CN116307858A - Mapping result quality inspection and scoring system - Google Patents
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Abstract
The invention discloses a mapping result quality inspection and scoring system, which belongs to the technical field of mapping information quality inspection, and comprises a mapping instrument, a user platform, an information recording module, a data verification module, a mapping evaluation module, a performance detection module, an operation examination module and an information printing module; the invention can improve the accuracy of the evaluation model and the efficiency of searching parameters, improves the grading accuracy of mapping results, does not need to manually set parameters and manually model, effectively reduces the workload of management staff, improves the working efficiency, can realize the acquisition of log information of user platforms of various systems, does not need to collect logs each time by management staff to perform configuration operation, shortens the waiting time of log analysis, can perform log analysis without professional knowledge of the management staff, and reduces the use limitation.
Description
Technical Field
The invention relates to the technical field of quality inspection of mapping information, in particular to a quality inspection and scoring system for mapping achievements.
Background
Mapping refers to measuring, collecting and drawing the shape, size, spatial position, attribute and the like of natural geographic elements or surface artificial facilities; mapping has wide application in economic construction and national defense construction. In urban and rural construction planning, homeland resource utilization, environmental protection and other works, various maps for land measurement and mapping must be performed for planning and management. In the construction of geological exploration, mineral development, water conservancy, traffic and the like, control measurement, mine measurement, route measurement and topographic map drawing are required to be carried out for geological investigation and various building design construction, and in order to ensure that the land form and the landform are reflected correctly, completely and truly by the result of the drawing product, the quality of the product and the measurement precision and reliability are continuously improved; the mapping result quality inspection and scoring system becomes one of the main assessment tools of each mapping result management unit.
Through retrieval, chinese patent number CN108509538A discloses a mapping result quality inspection and scoring system, and the invention realizes automatic format conversion and coordinate conversion classification processing on common data, so that the inspection and scoring of standard data and nonstandard data are realized, the compatibility is good, the degree of automation is high, but the mapping result evaluation accuracy is low, the workload of management staff is increased, and the working efficiency is reduced; in addition, the existing mapping result quality inspection and scoring system cannot collect log information of user platforms of different systems, management staff is required to collect logs each time to perform configuration operation, and the use limitation is large, so that the mapping result quality inspection and scoring system is provided.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a mapping result quality inspection and scoring system.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the system comprises a mapping instrument, a user platform, an information recording module, a data verification module, a mapping evaluation module, a performance detection module, an operation examination module and an information printing module;
the surveying instrument is used for collecting relevant ground information by surveyors;
the user platform is used for checking collected mapping data, data detection and scoring results;
the information recording module is used for processing and recording the collected mapping data;
the data verification module is used for performing conversion verification on each set of mapping data;
the mapping evaluation module is used for evaluating the quality of related mapping data according to the verification result;
the performance detection module is used for detecting the evaluation performance of the mapping evaluation module;
the operation examination module is used for collecting and detecting log information of the user platform and interrupting an operation instruction with risk according to a detection result;
the information printing module is used for feeding relevant data back to the manager and printing the data.
As a further aspect of the present invention, the surveying instrument specifically includes a theodolite, a level, a plate instrument, and a total station.
As a further scheme of the invention, the information recording module processes and records the specific steps as follows:
step one: the information recording module receives mapping data acquired by each mapping instrument, then preprocesses each group of mapping data to convert the mapping data into data in a uniform format, and then records the generation time of each group of data;
step two: classifying the data of each group according to a preset time range, performing secondary classification processing on the classified mapping data of each group according to different areas, generating a plurality of groups of information tables by using the information record table, generating unique numbers by not generating each group of information tables, and simultaneously importing the classified data of each group into the corresponding information table for storage.
As a further aspect of the present invention, the data verification module performs the following specific steps:
step (1): the data verification module receives an information table to be processed, acquires parameters of a graphic object in mapping data recorded in the information table, and simultaneously sends each group of parameters to the GIS platform;
step (2): the GIS platform receives the parameters of each group, performs standard symbolization and drawing expression, and performs graphic restoration on the objects described in the drawing data to obtain drawing results to be verified;
step (3): the data verification module defines a coordinate system of the mapping result to be verified as an original coordinate system, defines a coordinate system of the mapping data as a target coordinate system, and projects the mapping result to be verified in the original coordinate system into the target coordinate system through a correlation conversion relation;
step (4): generating a corresponding inspection scheme, quality elements, quality sub-elements, configuration quality sub-elements and weights according to the type of the mapping result to be verified, then judging the mapping result to be verified according to the existing standard specification and mapping experience, marking the error mapping result, and simultaneously carrying out dislocation description.
As a further scheme of the invention, the specific evaluation steps of the quality of the mapping data by the mapping evaluation module are as follows:
step (1): constructing a convolutional neural network, importing an evaluation standard uploaded by a manager into the convolutional neural network, and performing learning training through input, convolution, pooling, full connection and output to obtain an evaluation model;
step (2): the evaluation model receives the verified mapping result, dislocation description and error quantity, performs feature dimension reduction processing on each group of data, screens out data with poor characterization capability according to the processing result, and then divides the residual data into a training set and a testing set;
step (3): the training set is standardized to obtain training samples, then the training samples are input into an evaluation model, specific parameters of the model are set, the evaluation model is trained by adopting a long-term iteration method, the testing set is input into the trained model, and evaluation scores and evaluation grades are output.
As a further scheme of the invention, the assessment grade classification in the step (3) is specifically that 95-100 is classified as a superior grade; 80 to 95 are classified into good grade products; 65 to 80 are divided into qualified products; 60 to 65 is divided into basic qualified products; and the product is a defective product below 60 minutes.
As a further scheme of the invention, the specific steps of evaluating the performance detection by the performance detection module are as follows:
step I: the performance detection module receives the operation data of the fine mapping evaluation module, adopts a focus loss function to perform loss calculation, if the calculation result does not meet the expected value, collects past evaluation records of the mapping evaluation module, selects a group of past evaluation records as observation data, and uses the rest data to fit a test model;
step II: verifying the accuracy of the test model by using the observation data, and repeatedly calculating the evaluation capability of the test model through root mean square error for a plurality of times to obtain a plurality of groups of accuracy parameters, and listing all possible data samples according to a preset learning rate and step length;
step III: selecting any subset as a test set, selecting the rest subsets as a training set, predicting the test set after training a model, counting the root mean square error of a test result, replacing the test set with another subset, selecting the rest subsets as the training set, counting the root mean square error again until all data samples are predicted once, selecting the corresponding combined parameter with the minimum root mean square error as the optimal parameter in the data interval, and replacing the original parameter of the evaluation model in the mapping evaluation module.
As a further aspect of the present invention, the log information detection of the operation review module specifically includes the following steps:
s1: the log detection module deploys related log acquisition plug-ins on user platforms of different systems or acquires log data recorded in the user platforms of different systems through a syslog server, and uses log stack to screen out log information meeting the setting conditions of management personnel;
s2: processing the residual log data into log information in a unified format, then matching the user operation behaviors recorded in the log information with abnormal behavior characteristics, generating corresponding alarm information according to the matching result, calculating risk scores of all alarm information and outputting calculation results.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, a convolutional neural network is constructed through a mapping evaluation module, an evaluation model is generated according to evaluation standards uploaded by management staff, the evaluation model receives verified mapping results, dislocation descriptions and error quantity to output evaluation scores and registration corresponding to the mapping results, a performance detection module receives operation data of the fine mapping evaluation module and carries out loss calculation by adopting a focus loss function, if the calculation results do not meet expected values, a past evaluation record of the mapping evaluation module is collected to fit a group of test models, a plurality of groups of precision parameters are obtained through the test models, all possible data samples are listed according to preset learning rates and step sizes, root mean square errors of all the groups of data samples are counted, and the corresponding combined parameters are selected as optimal parameters in a data interval to replace original parameters of the evaluation model, so that the precision of the evaluation model and the efficiency of searching parameters can be improved, the accuracy of the mapping results is improved, meanwhile, manual setting of parameters is not needed, the workload of the management staff is effectively reduced, and the working efficiency is improved;
2. according to the invention, related log acquisition plug-ins are deployed on user platforms of different systems through a log detection module or log data recorded in the user platforms of different systems are acquired through a syslog server, log information meeting the set conditions of management personnel is screened out by using log stack, the rest log data are processed into log information in a unified format, then the user operation behaviors recorded in the log information are matched with abnormal behavior characteristics, corresponding alarm information is generated according to the matching result, meanwhile, risk scores of all alarm information are calculated and calculation results are output, the log information of the user platforms of various systems can be acquired, management personnel do not need to collect logs each time, log analysis waiting time is shortened, log analysis can be performed without professional knowledge of the management personnel, and the use limitation is reduced.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention.
FIG. 1 is a system block diagram of a mapping outcome quality inspection and scoring system in accordance with the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
Example 1
Referring to fig. 1, a mapping outcome quality inspection and scoring system includes a mapping instrument, a user platform, an information recording module, a data verification module, a mapping evaluation module, a performance detection module, an operational review module, and an information printing module.
The surveying instrument is used for surveying staff to gather relevant ground information.
In this embodiment, the surveying instrument specifically includes a theodolite, a level, a plate instrument, and a total station.
The user platform is used for checking the collected mapping data, data detection and scoring results; the information recording module is used for processing and recording the collected mapping data.
Specifically, the information recording module receives mapping data collected by each mapping instrument, then preprocesses each group of mapping data to convert the mapping data into data in a unified format, then records the generation time of each group of data, classifies each group of data according to a preset time range, performs secondary classification processing on each group of classified mapping data according to different areas, generates a plurality of groups of information tables by using the information recording table, generates no unique number by using each group of information tables, and simultaneously imports each group of classified data into the corresponding information table for storage.
The data verification module is used for performing conversion verification on each set of mapping data.
Specifically, the data verification module receives an information table to be processed, acquires parameters of graphic objects in mapping data recorded in the information table, simultaneously transmits all groups of parameters to the GIS platform, then the GIS platform receives all groups of parameters, performs standard symbolization and drawing expression, and performs graphic restoration on objects described in the mapping data to acquire a mapping result to be verified, the data verification module defines a coordinate system of the mapping result to be verified as an original coordinate system, defines the coordinate system of the mapping data as a target coordinate system, projects the mapping result to be verified in the original coordinate system into the target coordinate system through a relevant conversion relation, generates a corresponding inspection scheme, quality elements, quality subelements, configuration quality subelements and weights according to the type of the mapping result to be verified, then performs interpretation on the mapping result to be verified according to the existing standard specification and experience, marks the error mapping result, and simultaneously performs dislocation description.
The mapping evaluation module is used for evaluating the quality of the related mapping data according to the verification result.
Specifically, a mapping evaluation module builds a convolutional neural network, introduces evaluation standards uploaded by a manager into the convolutional neural network, carries out learning training through input, convolution, pooling, full connection and output to obtain an evaluation model, then receives verified mapping results, dislocation descriptions and error numbers, carries out feature dimension reduction processing on each group of data, screens out data with poor characterization capability according to processing results, divides the remaining data into a training set and a test set, carries out standardization processing on the training set to obtain training samples, then inputs the training samples into the evaluation model, sets specific parameters of the model, trains the evaluation model by adopting a long-term iteration method, inputs the test set into the trained model, and outputs evaluation scores and evaluation grades.
It should be further described that the evaluation grade classification is specifically 95-100 classified as a superior grade; 80 to 95 are classified into good grade products; 65 to 80 are divided into qualified products; 60 to 65 is divided into basic qualified products; and the product is a defective product below 60 minutes.
Example 2
Referring to fig. 1, a mapping outcome quality inspection and scoring system includes a mapping instrument, a user platform, an information recording module, a data verification module, a mapping evaluation module, a performance detection module, an operational review module, and an information printing module.
The performance detection module is used for detecting the evaluation performance of the mapping evaluation module.
Specifically, the performance detection module receives the operation data of the fine mapping evaluation module, performs loss calculation by adopting a focus loss function, collects the past evaluation records of the mapping evaluation module if the calculation result does not meet the expected value, then selects a group of the past evaluation records as observation data, uses the remaining data to simulate a test model, uses the observation data to verify the accuracy of the test model, repeatedly calculates the evaluation capability of the test model through root mean square error for a plurality of times to obtain a plurality of groups of accuracy parameters, lists all possible data samples according to a preset learning rate and step length, then selects any subset as a test set, uses the remaining subset as a training set, predicts the test set after the training model, counts the root mean square error of the test result, then replaces the test set with another subset, then uses the remaining subset as the training set, counts the root mean square error again until the test model is predicted once, and replaces the original parameters of the evaluation model in the mapping evaluation module by selecting the corresponding combination parameters with the minimum root mean square error as optimal parameters in a data interval.
The operation inspection module is used for collecting and detecting log information of the user platform and interrupting an operation instruction with risk according to a detection result.
Specifically, the log detection module deploys related log acquisition plug-ins on user platforms of different systems or acquires log data recorded in the user platforms of different systems through a syslog server, screens out log information meeting the set conditions of management personnel by using log stack, processes the remaining log data into log information in a unified format, matches the user operation behaviors recorded in the log information with abnormal behavior features, generates corresponding alarm information according to the matching result, calculates risk scores of all alarm information, and outputs a calculation result.
The information printing module is used for feeding back relevant data to the manager and printing the data.
Claims (8)
1. The system for checking and scoring the quality of the surveying and mapping achievements is characterized by comprising a surveying and mapping instrument, a user platform, an information recording module, a data verification module, a surveying and mapping evaluation module, a performance detection module, an operation examination module and an information printing module;
the surveying instrument is used for collecting relevant ground information by surveyors;
the user platform is used for checking collected mapping data, data detection and scoring results;
the information recording module is used for processing and recording the collected mapping data;
the data verification module is used for performing conversion verification on each set of mapping data;
the mapping evaluation module is used for evaluating the quality of related mapping data according to the verification result;
the performance detection module is used for detecting the evaluation performance of the mapping evaluation module;
the operation examination module is used for collecting and detecting log information of the user platform and interrupting an operation instruction with risk according to a detection result;
the information printing module is used for feeding relevant data back to the manager and printing the data.
2. The surveying and mapping effort quality inspection and scoring system of claim 1, wherein the surveying instrument specifically comprises a theodolite, a level, a flatbed, and a total station.
3. The system for quality inspection and scoring of achievements of surveying and mapping according to claim 2, wherein the information recording module processes the records as follows:
step one: the information recording module receives mapping data acquired by each mapping instrument, then preprocesses each group of mapping data to convert the mapping data into data in a uniform format, and then records the generation time of each group of data;
step two: classifying the data of each group according to a preset time range, performing secondary classification processing on the classified mapping data of each group according to different areas, generating a plurality of groups of information tables by using the information record table, generating unique numbers by not generating each group of information tables, and simultaneously importing the classified data of each group into the corresponding information table for storage.
4. The system for quality inspection and scoring of a mapping outcome of claim 3, wherein the data verification module transitions and verifies the specific steps as follows:
step (1): the data verification module receives an information table to be processed, acquires parameters of a graphic object in mapping data recorded in the information table, and simultaneously sends each group of parameters to the GIS platform;
step (2): the GIS platform receives the parameters of each group, performs standard symbolization and drawing expression, and performs graphic restoration on the objects described in the drawing data to obtain drawing results to be verified;
step (3): the data verification module defines a coordinate system of the mapping result to be verified as an original coordinate system, defines a coordinate system of the mapping data as a target coordinate system, and projects the mapping result to be verified in the original coordinate system into the target coordinate system through a correlation conversion relation;
step (4): generating a corresponding inspection scheme, quality elements, quality sub-elements, configuration quality sub-elements and weights according to the type of the mapping result to be verified, then judging the mapping result to be verified according to the existing standard specification and mapping experience, marking the error mapping result, and simultaneously carrying out dislocation description.
5. The system of claim 4, wherein the mapping assessment module specifically assesses the quality of the mapping data as follows:
step (1): constructing a convolutional neural network, importing an evaluation standard uploaded by a manager into the convolutional neural network, and performing learning training through input, convolution, pooling, full connection and output to obtain an evaluation model;
step (2): the evaluation model receives the verified mapping result, dislocation description and error quantity, performs feature dimension reduction processing on each group of data, screens out data with poor characterization capability according to the processing result, and then divides the residual data into a training set and a testing set;
step (3): the training set is standardized to obtain training samples, then the training samples are input into an evaluation model, specific parameters of the model are set, the evaluation model is trained by adopting a long-term iteration method, the testing set is input into the trained model, and evaluation scores and evaluation grades are output.
6. The system for quality inspection and scoring of mapping achievements of claim 5, wherein the classification of the assessment level in step (3) is specifically 95-100 into a top grade; 80 to 95 are classified into good grade products; 65 to 80 are divided into qualified products; 60 to 65 is divided into basic qualified products; and the product is a defective product below 60 minutes.
7. The system for quality inspection and scoring of achievements of surveying according to claim 1, wherein the performance detection module evaluates performance detection as follows:
step I: the performance detection module receives the operation data of the fine mapping evaluation module, adopts a focus loss function to perform loss calculation, if the calculation result does not meet the expected value, collects past evaluation records of the mapping evaluation module, selects a group of past evaluation records as observation data, and uses the rest data to fit a test model;
step II: verifying the accuracy of the test model by using the observation data, and repeatedly calculating the evaluation capability of the test model through root mean square error for a plurality of times to obtain a plurality of groups of accuracy parameters, and listing all possible data samples according to a preset learning rate and step length;
step III: selecting any subset as a test set, selecting the rest subsets as a training set, predicting the test set after training a model, counting the root mean square error of a test result, replacing the test set with another subset, selecting the rest subsets as the training set, counting the root mean square error again until all data samples are predicted once, selecting the corresponding combined parameter with the minimum root mean square error as the optimal parameter in the data interval, and replacing the original parameter of the evaluation model in the mapping evaluation module.
8. The system for quality inspection and scoring of a mapping effort of claim 1, wherein the operation review module log information detection comprises the specific steps of:
s1: the log detection module deploys related log acquisition plug-ins on user platforms of different systems or acquires log data recorded in the user platforms of different systems through a syslog server, and uses log stack to screen out log information meeting the setting conditions of management personnel;
s2: processing the residual log data into log information in a unified format, then matching the user operation behaviors recorded in the log information with abnormal behavior characteristics, generating corresponding alarm information according to the matching result, calculating risk scores of all alarm information and outputting calculation results.
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| CN117668273B (en) * | 2024-02-01 | 2024-04-19 | 山东省国土测绘院 | Mapping result management method |
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