CN112084225A - Intelligent processing method and system of big data based sharing platform and readable storage medium - Google Patents
Intelligent processing method and system of big data based sharing platform and readable storage medium Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
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- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
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- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D2700/00—Means for sensing or measuring; Sensors therefor
- F25D2700/12—Sensors measuring the inside temperature
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Abstract
The invention relates to an intelligent processing method, a system and a readable storage medium of a big data-based sharing platform, comprising the following steps: acquiring user preference information through big data analysis, generating an original database, and establishing a preset model; analyzing a preset model, automatically generating a processing mode to obtain processing information, identifying the food material type through an image, generating a corresponding refrigeration mode, and obtaining refrigeration information; comparing the refrigeration information with preset information to obtain a deviation rate; judging whether the deviation rate is greater than a preset deviation rate threshold value or not; if the correction information is larger than the preset correction information, the correction information is automatically acquired, and the processing information is reversely corrected according to the correction information to obtain result information.
Description
Technical Field
The invention relates to an intelligent processing method of a sharing platform, in particular to an intelligent processing method, an intelligent processing system and a readable storage medium of a sharing platform based on big data.
Background
The sharing fruit juice mixer is matched with automatic juicing, intelligent cleaning and self-service vending intelligent hardware, common fruit juicing can be basically met according to fruit types on the market, users with different tastes can be met to the maximum extent, and the intelligent equipment is compatible with juicing of various fruits and more conveniently meets use habits of the users.
The full-automatic intelligent operation can not be realized to present fruit juice extractor, and is preparing the back with eating the material in advance, can't refrigerate fresh-keeping to eating the material, is difficult to adopt different cold-stored mode to different edible materials in addition, eats the fresh degree of material and can't reach the requirement, causes the new freshness decline of fruit juice.
In order to realize accurate control to sharing fruit juice mixer, need develop a section and control rather than assorted system, can be to the cold-stored mode that food material kind intelligence generation corresponds of difference through this system to realize eating the better fresh-keeping of material, but in carrying out the control process, how to realize accurate control, the cold-stored problem that can't wait to solve of intelligence food material that realizes sharing platform all is urgent.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides an intelligent processing method and system of a big data based sharing platform and a readable storage medium.
In order to achieve the purpose, the invention adopts the technical scheme that: an intelligent processing method based on a big data sharing platform comprises the following steps:
acquiring user preference information through big data analysis, generating an original database, and establishing a preset model;
analyzing the preset model, automatically generating a processing mode to obtain processing information,
identifying the food material types through images, generating a corresponding refrigeration mode, and obtaining refrigeration information;
comparing the refrigeration information with preset information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the correction information is automatically acquired, and the processing information is reversely corrected according to the correction information to obtain result information.
Preferably, a first mark point and a second mark point are arranged in different areas of the refrigerating space, the first mark point monitors and tracks first refrigerating temperature information in the corresponding area, and the second mark point monitors and tracks second refrigerating temperature information in the corresponding area;
comparing the first refrigeration temperature information with the second refrigeration temperature information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the first refrigeration temperature information and the second refrigeration temperature information.
Preferably, the preset model includes a convolutional neural network model, specifically:
acquiring user crowd attributes through big data analysis, and acquiring user data through cloud computing;
inputting user data into a convolutional neural network model, training the convolutional neural network model through big data to obtain a feedback signal, and acquiring feedback information;
and setting a refrigeration processing mode according to the feedback information.
Preferably, the user population attribute information includes one or a combination of two or more of user preference, user weight information, user taboo information, and user gender information.
Preferably, the processing information is reversely corrected according to the correction information to obtain result information; further comprising:
dividing a preset area into N different sub-areas;
calculating the food material type and the matching characteristic of each subregion to obtain a characteristic value;
comparing the eigenvalue difference rate for each different sub-region;
classifying the sub-regions smaller than the threshold value of the feature value difference rate into regions of the same category;
raw database information for regions of the same category is obtained,
calculating correction parameters according to the original database information;
and feeding back optimization result information according to the correction parameters.
Preferably, obtaining the current working state parameters of the sharing platform and generating original state data;
transmitting the original state data to a database through a remote server, and performing analysis and statistics to form a statistical table;
acquiring real-time working state parameters of a sharing platform and generating real-time state data;
comparing the real-time state data with the original state data to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the working state parameters of the shared platform.
The second aspect of the present invention also provides an intelligent processing system based on a big data sharing platform, which includes: the intelligent processing method program based on the big data sharing platform comprises a memory and a processor, wherein the memory comprises the intelligent processing method program based on the big data sharing platform, and when the intelligent processing method program based on the big data sharing platform is executed by the processor, the following steps are realized:
acquiring user preference information through big data analysis, generating an original database, and establishing a preset model;
analyzing the preset model, automatically generating a processing mode to obtain processing information,
identifying the food material types through images, generating a corresponding refrigeration mode, and obtaining refrigeration information;
comparing the refrigeration information with preset information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the correction information is automatically acquired, and the processing information is reversely corrected according to the correction information to obtain result information.
Preferably, a first mark point and a second mark point are arranged in different areas of the refrigerating space, the first mark point monitors and tracks first refrigerating temperature information in the corresponding area, and the second mark point monitors and tracks second refrigerating temperature information in the corresponding area;
comparing the first refrigeration temperature information with the second refrigeration temperature information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the first refrigeration temperature information and the second refrigeration temperature information.
Preferably, obtaining the current working state parameters of the sharing platform and generating original state data;
transmitting the original state data to a database through a remote server, and performing analysis and statistics to form a statistical table;
acquiring real-time working state parameters of a sharing platform and generating real-time state data;
comparing the real-time state data with the original state data to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the working state parameters of the shared platform.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of an intelligent processing method for a big data based sharing platform, and when the program of the intelligent processing method for the big data based sharing platform is executed by a processor, the method implements any one of the steps of the method for the intelligent processing for the big data based sharing platform.
The invention solves the defects in the background technology, and has the following beneficial effects:
(1) through big data acquisition, analysis, the generative model, the model can be generated through neural network training, carries out neural network training in-process, can make the continuous study of updating of neural network through the continuous update of data, improves the precision of automatic handling, makes the system can carry out continuous study, and the audience taste of laminating more, the automatic cold-stored information of recommending of system can be liked by the audience simultaneously.
(2) To different fruit types, according to big data analysis fruit characteristic, distribute in the subregion of difference to carry out feedback optimization to the information of handling through correction information, make the cold-stored mode be applicable to different fruit vegetables types, thereby laminate different use crowds more, intelligent degree is higher.
(3) Through setting up the mark point in the different positions department in cold-stored space, carry out the cold-stored temperature monitoring in cold-stored space different regions, when great difference appears in the cold-stored temperature in the different cold-stored district in same cold-stored space, through the adjustment to cold-stored temperature for the cold-stored temperature of cold-stored space each position department is in suitable scope, guarantees that the temperature in the cold-stored space is even, can not cause the fruit vegetables in the cold-stored space deviation to appear, and cold-stored effect is better.
(4) The difference between the current working state parameter and the real-time working state parameter of the sharing platform is monitored, a corresponding statistical table is formed, the two working state parameters are compared, and when a large deviation occurs, the working state parameter of the sharing platform is adjusted, so that the sharing platform is always in a better working state.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of an intelligent processing method based on a big data sharing platform according to the invention;
FIG. 2 shows a flow chart of a refrigeration processing method;
fig. 3 shows a flow chart of a food material distribution method;
FIG. 4 is a flow chart illustrating a shared platform operating state parameter adjustment method;
FIG. 5 illustrates a block diagram of an intelligent processing system based on a big data shared platform.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
FIG. 1 is a flow chart showing an intelligent processing method based on a big data sharing platform according to the invention.
As shown in fig. 1, a first aspect of the present invention provides an intelligent processing method for a big data based shared platform, including:
s102, acquiring user preference information through big data analysis, generating an original database, and establishing a preset model;
s104, analyzing the preset model, automatically generating a processing mode to obtain processing information,
s106, identifying the food material types through images, generating a corresponding refrigeration mode, and obtaining refrigeration information;
s108, comparing the refrigeration information with preset information to obtain a deviation rate;
s110, judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and S112, if the sum is larger than the preset value, automatically acquiring correction information, and reversely correcting the processing information according to the correction information to obtain result information.
It should be noted that, different food materials are refrigerated in different manners to generate corresponding refrigeration information, the refrigeration information may be parameter information such as refrigeration temperature, refrigeration time, refrigeration manner, air humidity, air flow rate, etc., the type of the fruit is identified through an image, different refrigeration temperatures and refrigeration times are set for different fruit types, the refrigeration manner may be modified atmosphere refrigeration, that is, a method for prolonging the storage period of the fruit by adjusting ambient gas, the principle is that in a certain closed system, a modified gas different from normal atmosphere composition is obtained through various adjustment methods, such as carbon dioxide and hypoxia, so as to inhibit the physiological and biochemical processes of deterioration caused by the fruit itself or the microbial activity processes acting on the fruit, the refrigeration manner may also be reduced pressure refrigeration, but is not limited to these two refrigeration manners, and those skilled in the art can replace other refrigeration manners according to climate conditions or geographic environments or fruit types, for example, in different geographical environments, the refrigeration conditions of fruits and parts of vegetables are different, and for example, tropical and subtropical fruits and parts of vegetables are stored in a temperature range of 3-10 ℃ above the freezing point, and cold damage can occur.
It should be noted that identifying the food material type through the image includes collecting a multi-angle image of the food material through a camera as original image information of the food material, extracting a characteristic value from the multi-angle image, classifying the characteristic value into the same category when the deviation ratio is smaller than a preset value, identifying the food material type, generating a corresponding refrigeration mode for different food material types, monitoring the refrigeration information in real time in the refrigeration process, adjusting the refrigeration information through correction information when the refrigeration information has a deviation, dynamically adjusting the refrigeration information through the correction information, making the refrigeration information more fit with the food material type, and achieving a better refrigeration effect.
According to the embodiment of the invention, a first mark point and a second mark point are arranged in different areas of a refrigerating space, the first mark point monitors and tracks first refrigerating temperature information in the corresponding area, and the second mark point monitors and tracks second refrigerating temperature information in the corresponding area;
comparing the first refrigeration temperature information with the second refrigeration temperature information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the first refrigeration temperature information and the second refrigeration temperature information.
It should be noted that, through setting up the mark point in the different positions department in cold-stored space, carry out the cold-stored temperature monitoring in different regions in cold-stored space, when great difference appears in the cold-stored temperature in the different cold-stored district in same cold-stored space, through the adjustment to cold-stored temperature for the cold-stored temperature of each position department in cold-stored space is in suitable scope, guarantees that the temperature in the cold-stored space is even, can not cause the fruit vegetables in the cold-stored space to appear the deviation, and cold-stored effect is better.
It should be noted that the refrigerating space is divided into a plurality of spaces, food materials with different refrigerating conditions are stored in different refrigerating spaces, adaptive refrigeration can be performed according to the types and characteristics of the food materials, the food materials are kept fresh continuously, in addition, the food materials are divided into a plurality of sub-areas in the same refrigerating space, each sub-area can be used as an independent area, the refrigerating temperature in the sub-area is monitored by mark points in different sub-areas, when the refrigerating temperature deviation in different sub-areas is large, the refrigerating temperature of the sub-areas is adjusted through a system, so that the temperatures of the sub-areas in the refrigerating space tend to be the same or close, and the uniform temperature in the refrigerating space is ensured.
As shown in FIG. 2, the present invention discloses a flow chart of a refrigeration processing method;
according to the embodiment of the invention, the preset model comprises a convolutional neural network model, and specifically comprises the following steps:
s202, obtaining user crowd attributes through big data analysis, and obtaining user data through cloud computing;
s204, inputting user data into the convolutional neural network model, training the convolutional neural network model through big data to obtain a feedback signal, and acquiring feedback information;
and S206, setting a refrigeration processing mode according to the feedback information.
It should be noted that the user data can be analyzed in real time through the convolutional neural network model to obtain an optimal refrigeration mode, and the decision is updated in real time according to the feedback information, so that the autonomous learning capability of the system is greatly enhanced. The refrigeration information can also separate the user demands of different ages and sexes and the attention degree to different food materials according to the demands of different seasons, better targeted decision information is provided, the refrigeration processing mode selection accuracy is also greatly improved, specific refrigeration can be carried out along with the conditions such as time, regions and the like, and the refrigeration matching degree is higher.
According to the embodiment of the invention, the user crowd attribute information comprises one or more of user preference, user weight information, user taboo information or user gender information.
As shown in fig. 3, the present invention discloses a flow chart of a food material distribution method;
according to the embodiment of the invention, the processing information is reversely corrected according to the correction information to obtain result information; further comprising:
s302, dividing a preset area into N different sub-areas;
s304, calculating the food material type and the matching characteristic of each sub-area to obtain a characteristic value;
s306, comparing the characteristic value difference rate of each different sub-region;
s308, classifying the sub-regions smaller than the threshold of the feature value difference rate into regions of the same category;
s310, obtaining the original database information of the same category area,
s312, calculating correction parameters according to the original database information;
and S314, feeding back optimization result information according to the correction parameters.
It should be noted that, the present invention can also modify and optimize food material proportioning information according to modification parameters, the modified parameters are obtained by performing big data analysis according to different similar regions, and can be closer to actual values, a preset region is first determined, the preset region can be distinguished according to climate conditions, and can also be distinguished by human environments, a person skilled in the art can adjust according to actual needs, and then the region is divided into N sub-regions, the N sub-regions can be independent regions, and can also have regions with intersection, the range can be adjusted, different refrigeration modes are selected for food material characteristics in different regions, and feedback optimization is performed through modification parameters, so that result information is closer to actual values, the accuracy of intelligent refrigeration of the system is increased, for different fruit types, fruit characteristics are analyzed according to big data, the method is distributed into the refrigeration spaces in different sub-areas, and the database information is fed back and optimized through the correction parameters, so that the intelligent degree is high.
As shown in fig. 4, the present invention discloses a flow chart of a method for adjusting working state parameters of a sharing platform;
according to the embodiment of the invention, the current working state parameters of the sharing platform are obtained, and original state data are generated;
transmitting the original state data to a database through a remote server, and performing analysis and statistics to form a statistical table;
s402, acquiring real-time working state parameters of the sharing platform and generating real-time state data;
s404, comparing the real-time state data with the original state data to obtain a deviation rate;
s406, judging whether the deviation rate is greater than a preset deviation rate threshold value;
and S408, if the value is larger than the preset value, adjusting the working state parameters of the shared platform.
It should be noted that the working state parameters of the sharing platform include identification modes and identification time of the food materials; the refrigerating temperature, the refrigerating mode and the refrigerating time in the refrigerating space; the manner in which the food material is distributed to the corresponding refrigerated space, etc.
As shown in FIG. 5, the present invention discloses a block diagram of an intelligent processing system based on a big data sharing platform;
the second aspect of the present invention also provides an intelligent processing system 5 based on a big data sharing platform, where the system 5 includes: the storage 51 and the processor 52, the storage includes an intelligent processing method program based on the big data sharing platform, and when the intelligent processing method program based on the big data sharing platform is executed by the processor, the following steps are implemented:
acquiring user preference information through big data analysis, generating an original database, and establishing a preset model;
analyzing the preset model, automatically generating a processing mode to obtain processing information,
identifying the food material types through images, generating a corresponding refrigeration mode, and obtaining refrigeration information;
comparing the refrigeration information with preset information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the correction information is automatically acquired, and the processing information is reversely corrected according to the correction information to obtain result information.
It should be noted that, different food materials are refrigerated in different manners to generate corresponding refrigeration information, the refrigeration information may be parameter information such as refrigeration temperature, refrigeration time, refrigeration manner, air humidity, air flow rate, etc., the type of the fruit is identified through an image, different refrigeration temperatures and refrigeration times are set for different fruit types, the refrigeration manner may be modified atmosphere refrigeration, that is, a method for prolonging the storage period of the fruit by adjusting ambient gas, the principle is that in a certain closed system, a modified gas different from normal atmosphere composition is obtained through various adjustment methods, such as carbon dioxide and hypoxia, so as to inhibit the physiological and biochemical processes of deterioration caused by the fruit itself or the microbial activity processes acting on the fruit, the refrigeration manner may also be reduced pressure refrigeration, but is not limited to these two refrigeration manners, and those skilled in the art can replace other refrigeration manners according to climate conditions or geographic environments or fruit types, for example, in different geographical environments, the refrigeration conditions of fruits and parts of vegetables are different, and for example, tropical and subtropical fruits and parts of vegetables are stored in a temperature range of 3-10 ℃ above the freezing point, and cold damage can occur.
It should be noted that identifying the food material type through the image includes collecting a multi-angle image of the food material through a camera as original image information of the food material, extracting a characteristic value from the multi-angle image, classifying the characteristic value into the same category when the deviation ratio is smaller than a preset value, identifying the food material type, generating a corresponding refrigeration mode for different food material types, monitoring the refrigeration information in real time in the refrigeration process, adjusting the refrigeration information through correction information when the refrigeration information has a deviation, dynamically adjusting the refrigeration information through the correction information, making the refrigeration information more fit with the food material type, and achieving a better refrigeration effect.
According to the embodiment of the invention, a first mark point and a second mark point are arranged in different areas of a refrigerating space, the first mark point monitors and tracks first refrigerating temperature information in the corresponding area, and the second mark point monitors and tracks second refrigerating temperature information in the corresponding area;
comparing the first refrigeration temperature information with the second refrigeration temperature information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the first refrigeration temperature information and the second refrigeration temperature information.
It should be noted that, through setting up the mark point in the different positions department in cold-stored space, carry out the cold-stored temperature monitoring in different regions in cold-stored space, when great difference appears in the cold-stored temperature in the different cold-stored district in same cold-stored space, through the adjustment to cold-stored temperature for the cold-stored temperature of each position department in cold-stored space is in suitable scope, guarantees that the temperature in the cold-stored space is even, can not cause the fruit vegetables in the cold-stored space to appear the deviation, and cold-stored effect is better.
It should be noted that the refrigerating space is divided into a plurality of spaces, food materials with different refrigerating conditions are stored in different refrigerating spaces, adaptive refrigeration can be performed according to the types and characteristics of the food materials, the food materials are kept fresh continuously, in addition, the food materials are divided into a plurality of sub-areas in the same refrigerating space, each sub-area can be used as an independent area, the refrigerating temperature in the sub-area is monitored by mark points in different sub-areas, when the refrigerating temperature deviation in different sub-areas is large, the refrigerating temperature of the sub-areas is adjusted through a system, so that the temperatures of the sub-areas in the refrigerating space tend to be the same or close, and the uniform temperature in the refrigerating space is ensured.
According to the embodiment of the invention, the current working state parameters of the sharing platform are obtained, and original state data are generated;
transmitting the original state data to a database through a remote server, and performing analysis and statistics to form a statistical table;
acquiring real-time working state parameters of a sharing platform and generating real-time state data;
comparing the real-time state data with the original state data to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the working state parameters of the shared platform.
It should be noted that the working state parameters of the sharing platform include identification modes and identification time of the food materials; the refrigerating temperature, the refrigerating mode and the refrigerating time in the refrigerating space; the manner in which the food material is distributed to the corresponding refrigerated space, etc.
According to the embodiment of the invention, the processing information is reversely corrected according to the correction information to obtain result information; further comprising:
dividing a preset area into N different sub-areas;
calculating the food material type and the matching characteristic of each subregion to obtain a characteristic value;
comparing the eigenvalue difference rate for each different sub-region;
classifying the sub-regions smaller than the threshold value of the feature value difference rate into regions of the same category;
raw database information for regions of the same category is obtained,
calculating correction parameters according to the original database information;
and feeding back optimization result information according to the correction parameters.
It should be noted that, the present invention can also modify and optimize food material proportioning information according to modification parameters, the modified parameters are obtained by performing big data analysis according to different similar regions, and can be closer to actual values, a preset region is first determined, the preset region can be distinguished according to climate conditions, and can also be distinguished by human environments, a person skilled in the art can adjust according to actual needs, and then the region is divided into N sub-regions, the N sub-regions can be independent regions, and can also have regions with intersection, the range can be adjusted, different refrigeration modes are selected for food material characteristics in different regions, and feedback optimization is performed through modification parameters, so that result information is closer to actual values, the accuracy of intelligent refrigeration of the system is increased, for different fruit types, fruit characteristics are analyzed according to big data, the method is distributed into the refrigeration spaces in different sub-areas, and the database information is fed back and optimized through the correction parameters, so that the intelligent degree is high.
According to the embodiment of the invention, the preset model comprises a convolutional neural network model, and specifically comprises the following steps:
acquiring user crowd attributes through big data analysis, and acquiring user data through cloud computing;
inputting user data into a convolutional neural network model, training the convolutional neural network model through big data to obtain a feedback signal, and acquiring feedback information;
and setting a refrigeration processing mode according to the feedback information.
It should be noted that the user data can be analyzed in real time through the convolutional neural network model to obtain an optimal refrigeration mode, and the decision is updated in real time according to the feedback information, so that the autonomous learning capability of the system is greatly enhanced. The refrigeration information can also separate the user demands of different ages and sexes and the attention degree to different food materials according to the demands of different seasons, better targeted decision information is provided, the refrigeration processing mode selection accuracy is also greatly improved, specific refrigeration can be carried out along with the conditions such as time, regions and the like, and the refrigeration matching degree is higher.
According to the embodiment of the invention, the user crowd attribute information comprises one or more of user preference, user weight information, user taboo information or user gender information.
The third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes an intelligent processing method program for a big data based sharing platform, and when the intelligent processing method program for the big data based sharing platform is executed by a processor, the steps of the intelligent processing method for the big data based sharing platform are implemented.
The invention solves the defects in the background technology, and has the following beneficial effects:
through big data acquisition, analysis, the generative model, the model can be generated through neural network training, carries out neural network training in-process, can make the continuous study of updating of neural network through the continuous update of data, improves the precision of automatic handling, makes the system can carry out continuous study, and the audience taste of laminating more, the automatic cold-stored information of recommending of system can be liked by the audience simultaneously.
To different fruit types, according to big data analysis fruit characteristic, distribute in the subregion of difference to carry out feedback optimization to the information of handling through correction information, make the cold-stored mode be applicable to different fruit vegetables types, thereby laminate different use crowds more, intelligent degree is higher.
Through setting up the mark point in the different positions department in cold-stored space, carry out the cold-stored temperature monitoring in cold-stored space different regions, when great difference appears in the cold-stored temperature in the different cold-stored district in same cold-stored space, through the adjustment to cold-stored temperature for the cold-stored temperature of cold-stored space each position department is in suitable scope, guarantees that the temperature in the cold-stored space is even, can not cause the fruit vegetables in the cold-stored space deviation to appear, and cold-stored effect is better.
The difference between the current working state parameter and the real-time working state parameter of the sharing platform is monitored, a corresponding statistical table is formed, the two working state parameters are compared, and when a large deviation occurs, the working state parameter of the sharing platform is adjusted, so that the sharing platform is always in a better working state.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of a unit is only one logical function division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An intelligent processing method of a big data-based shared platform is characterized by comprising the following steps:
acquiring user preference information through big data analysis, generating an original database, and establishing a preset model;
analyzing the preset model, automatically generating a processing mode to obtain processing information,
identifying the food material types through images, generating a corresponding refrigeration mode, and obtaining refrigeration information;
comparing the refrigeration information with preset information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the correction information is automatically acquired, and the processing information is reversely corrected according to the correction information to obtain result information.
2. The intelligent processing method based on big data sharing platform according to claim 1, characterized in that:
setting a first mark point and a second mark point in different areas of the refrigerating space, wherein the first mark point monitors and tracks first refrigerating temperature information in the corresponding area, and the second mark point monitors and tracks second refrigerating temperature information in the corresponding area;
comparing the first refrigeration temperature information with the second refrigeration temperature information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the first refrigeration temperature information and the second refrigeration temperature information.
3. The intelligent processing method based on big data sharing platform according to claim 1, characterized in that:
the preset model comprises a convolutional neural network model, and specifically comprises the following steps:
acquiring user crowd attributes through big data analysis, and acquiring user data through cloud computing;
inputting user data into a convolutional neural network model, training the convolutional neural network model through big data to obtain a feedback signal, and acquiring feedback information;
and setting a refrigeration processing mode according to the feedback information.
4. The intelligent processing method based on big data sharing platform according to claim 1, characterized in that: the user crowd attribute information comprises one or more of user preference, user weight information, user taboo information or user gender information.
5. The intelligent processing method based on big data sharing platform according to claim 1, characterized in that: reversely correcting the processing information according to the correction information to obtain result information; further comprising:
dividing a preset area into N different sub-areas;
calculating the food material type and the matching characteristic of each subregion to obtain a characteristic value;
comparing the eigenvalue difference rate for each different sub-region;
classifying the sub-regions smaller than the threshold value of the feature value difference rate into regions of the same category;
raw database information for regions of the same category is obtained,
calculating correction parameters according to the original database information;
and feeding back optimization result information according to the correction parameters.
6. The intelligent processing method based on big data sharing platform according to claim 1, characterized in that: acquiring current working state parameters of a sharing platform and generating original state data;
transmitting the original state data to a database through a remote server, and performing analysis and statistics to form a statistical table;
acquiring real-time working state parameters of a sharing platform and generating real-time state data;
comparing the real-time state data with the original state data to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the working state parameters of the shared platform.
7. An intelligent processing system based on a big data sharing platform, which is characterized by comprising: the intelligent processing method program based on the big data sharing platform comprises a memory and a processor, wherein the memory comprises the intelligent processing method program based on the big data sharing platform, and when the intelligent processing method program based on the big data sharing platform is executed by the processor, the following steps are realized:
acquiring user preference information through big data analysis, generating an original database, and establishing a preset model;
analyzing the preset model, automatically generating a processing mode to obtain processing information,
identifying the food material types through images, generating a corresponding refrigeration mode, and obtaining refrigeration information;
comparing the refrigeration information with preset information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the correction information is automatically acquired, and the processing information is reversely corrected according to the correction information to obtain result information.
8. The intelligent processing system based on big data sharing platform of claim 7, wherein: setting a first mark point and a second mark point in different areas of the refrigerating space, wherein the first mark point monitors and tracks first refrigerating temperature information in the corresponding area, and the second mark point monitors and tracks second refrigerating temperature information in the corresponding area;
comparing the first refrigeration temperature information with the second refrigeration temperature information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the first refrigeration temperature information and the second refrigeration temperature information.
9. The intelligent processing system based on big data sharing platform of claim 7, wherein:
acquiring current working state parameters of a sharing platform and generating original state data;
transmitting the original state data to a database through a remote server, and performing analysis and statistics to form a statistical table;
acquiring real-time working state parameters of a sharing platform and generating real-time state data;
comparing the real-time state data with the original state data to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
and if so, adjusting the working state parameters of the shared platform.
10. A computer-readable storage medium characterized by: the computer readable storage medium includes a big data based sharing platform intelligent processing method program, and when the big data based sharing platform intelligent processing method program is executed by a processor, the steps of the big data based sharing platform intelligent processing method according to any one of claims 1 to 6 are realized.
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