CN111680855A - A method and system for automatic detection and early warning of project whole process risk - Google Patents

Abstract

The invention provides a method and a system for automatically detecting and warning risks in the whole process of a project, wherein the method for automatically detecting and warning risks in the whole process of the project comprises the following steps: s1: carrying out data analysis and mining on the enterprise-level full-service data set; s2: establishing a suspicious point analysis model according to an audit service scene; s3: scanning the mined data based on the suspicious point analysis model to obtain suspicious points; s4: and visually displaying the obtained suspicious points to provide decision information for a decision department.

Description

A method and system for automatic detection and early warning of project whole process risk

technical field

The invention relates to the field of risk monitoring, in particular to a method and system for automatic detection and early warning of risks in the whole process of a project.

Background technique

With the continuous improvement of enterprise informatization level, the coverage of audit business continues to expand. The audit system exists through integration with a single business system. Due to the low data processing efficiency, cross-system data analysis and automatic comparison scanning cannot be realized, and the scope of support for business is limited. , it is difficult for auditors to find problems, and data analysis between systems is mainly performed by manual comparison, resulting in low work efficiency.

In order to solve the above-mentioned defects of the existing technical problems, it is necessary to propose a method and device for automatic detection and early warning of risks in the whole process of the project.

SUMMARY OF THE INVENTION

In view of this, the purpose of the present invention is to propose a method and device for automatic detection and early warning of risks in the whole process of a project, and to construct a cross-professional, cross-business, cross-system, and cross-dimension based audit business model using "MPP + big data" technology. Data analysis rules, realize the automatic detection of risks in the whole process of engineering projects, quickly form doubts and problems existing in each node of the whole process of the monitored object, and visualize them. Efficiency, give full play to the role of intelligent analysis and auxiliary decision-making, and improve user experience at the same time.

In order to achieve the above object, the first aspect of the present invention proposes a method for automatic detection and early warning of project whole process risk, wherein the automatic detection and early warning method for project whole process risk includes:

S1: Data analysis and mining of enterprise-level full-service data sets;

S2: According to the audit business scenario, establish a doubt analysis model;

S3: Scan the mined data based on the doubt analysis model to obtain doubts;

S4: Visually display the obtained doubts to provide decision-making information for decision-making departments.

In the above-mentioned method for automatic detection and early warning of risks in the whole process of a project, in step S1, the enterprise-level full-service data set is formed based on the MPP big data technology architecture by relying on the enterprise-level full-service unified data center.

In the above-mentioned method for automatic detection and early warning of risks in the whole process of a project, in step S2, the enterprise-level full-service data set is cleaned, converted, calculated and processed to form a multi-service scenario set of audit operations through big data technology.

In the above-mentioned method for automatic risk detection and early warning in the whole process of a project, the step S2 includes: constructing a multi-dimensional doubt analysis model that is cross-professional, cross-business, and cross-system according to the audit requirements of the whole process of the project.

The above-mentioned method for automatic detection and early warning of risks in the whole process of the project, wherein the step S3 includes: comparing the mined data with the attention indicators and risk detection points in the whole process of the project based on the doubt analysis model to obtain doubts. .

The second aspect of the present invention provides an automatic detection and early warning system for project whole process risk, wherein the automatic detection and early warning system for project whole process risk includes:

The data analysis and mining module is used for data analysis and mining of enterprise-level full-service data sets;

Establish a doubt analysis module, which is used to establish a doubt analysis model according to the audit business scenario;

an acquisition module for suspicious points, which is used to scan the mined data based on the suspicious point analysis model to acquire suspicious points;

The visualization module is used to visualize the acquired doubts to provide decision-making information for decision-making departments.

In the above-mentioned automatic risk detection and early warning system for the whole process of the project, the enterprise-level full-service data set is formed by relying on the enterprise-level full-service unified data center and based on the MPP big data technology architecture.

A third aspect of the present invention provides a terminal device, wherein the terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the When the processor executes the computer program, the steps of the above-mentioned method for automatic detection and early warning of project whole process risks are realized.

A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the above-mentioned project whole process risk is realized Steps for automatic detection of alert methods.

In the prior art, under normal circumstances, the audit work mainly relies on a single business system for data integration and analysis, and needs to check the paper documents offline, which consumes a lot of audit human resources, and it is difficult to improve the audit work efficiency.

The technical scheme of automatic risk detection and early warning in the whole project process of the present invention is different from the previous audit work. By sorting out the focus indicators and risk detection points in the project process, it helps the auditors to trace the risk data of each stage of the project, quickly locates the problem and doubts, improves the audit work efficiency and saves money. Audit costs, reduce audit risks, improve resource utilization, and give full play to audit functions. At the same time, the automatic risk detection and early warning technology in the whole process of the project has broken through the barriers between businesses, realized cross-business data analysis and mining, and improved the level of data-based auditing.

Description of drawings

1 is a flowchart of an automatic detection and early warning method for project whole process risk according to an embodiment of the present invention;

Fig. 2 is the application example diagram of the project whole process risk automatic detection and early warning system according to the embodiment of the present invention;

Fig. 3 is the application example diagram of the automatic detection and early warning of project whole process risk according to the embodiment of the present invention;

4 is a flowchart of an automatic detection and early warning method for project whole process risk according to an embodiment of the present invention;

5 is a schematic structural diagram of an automatic detection and early warning system for project whole process risk according to an embodiment of the present invention; and

FIG. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

The following describes in detail the embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but not to be construed as a limitation of the present invention.

It will be understood by those skilled in the art that the singular forms "a", "an", "the" and "the" as used herein can include the plural forms as well, unless expressly stated otherwise. It will further be understood that when we refer to an element as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Furthermore, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combination of one or more of the associated listed items.

It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities with the same name but not the same or non-identical parameters. It can be seen that "first" and "second" It is only for the convenience of expression and should not be construed as a limitation to the embodiments of the present invention, and subsequent embodiments will not describe them one by one.

The technical solutions of the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

As shown in Figure 1, the present invention proposes an automatic detection and early warning method for the whole process risk of a project, wherein the automatic detection and early warning method for the whole process risk of the project includes:

S1: Data analysis and mining of enterprise-level full-service data sets;

S2: According to the audit business scenario, establish a doubt analysis model;

S3: Scan the mined data based on the doubt analysis model to obtain doubts;

S4: Visually display the obtained doubts to provide decision-making information for decision-making departments.

Further, the above steps are described in detail in the specific embodiments of the present invention. S1: Use big data platform analysis tools, ETL and other methods to conduct data analysis and mining on enterprise-level full-service data sets, and obtain the subject data of audit business scenarios;

S2: Based on the audit guidelines, combined with the list of audit issues over the years, and in accordance with the current laws, regulations and rules, establish a doubt analysis model;

S3: Scan the mined data based on the doubt analysis model to obtain doubts;

S4: Visually display the obtained doubts to provide decision-making information for decision-making departments.

The innovation point of this application mainly refers to the cross-system, cross-discipline, and cross-business data analysis and mining of enterprise-level full-service data sets; specifically, data analysis and mining include establishing an audit business model, and through data integration means, from the enterprise-level full-scale data analysis and mining. The business data set captures the data to the audit data mart to support the audit data scenario; builds a doubt analysis model according to the audit business scenario, and realizes the whole process scanning and result visualization of the engineering project through big data technology; specifically, after the user specifies the project, The system retrieves the system's full audit model through the project number. If there are doubts in the scanned project, the system will remind you of the red doubtful problem in the project stage, and provide a list and quantity of doubtful points. After the scanning is completed, the user can intuitively see which stages of the project have doubts in the whole process. , and through the scanning result list, the number of doubtful points can be penetrated to view the detailed information of doubtful points, so as to provide decision-making information for decision-making departments in a timely and accurate manner, realize remote online auditing, improve auditing work ability, quality and efficiency, and give full play to the role of auditing supervision.

Further, in step S1, relying on the enterprise-level full-service unified data center and based on the MPP big data technology architecture, the enterprise-level full-service data set is formed.

Further, in step S2, through the big data technology, the enterprise-level full-service data set is cleaned, converted, calculated and processed to form an audit job multi-service scenario set.

Further, the above-mentioned step S2 includes: constructing a multi-dimensional doubt analysis model that is cross-professional, cross-business, and cross-system according to the audit requirements of the whole process of the project.

In a specific embodiment of the present invention, the step S3 includes: comparing the mined data with the attention indicators and risk detection points in the whole process of the project based on the doubt analysis model to obtain doubts.

In the prior art, the business data required by the audit business in the past were scattered in various business systems (involving 13 business systems such as ERP, financial management and control, planning system, infrastructure system, and economic and legal system), and the audit operation system mainly covered ERP. limited. Relying on SAP and other business sources to discover audit clues, manually compare data, and check paper documents offline, it consumes a lot of audit human resources, and the audit work efficiency is low. Cross-system and cross-business data analysis cannot be achieved, and it is difficult to find problems. With the continuous exploration of audit informatization, a combination of audit system and operating system is gradually adopted. Data comparison and analysis, engineering operation tools only cover the ERP system, the coverage is limited, and cross-system comparison and analysis cannot be achieved. Manual comparison is still required, and personal empirical judgment.

This application relies on the enterprise-level full-service unified data center to realize the sharing and integration of services. Based on this, it is convenient to realize data analysis and mining, and then based on the MPP+ big data technology architecture (MPP refers to large-scale parallel processing, mainly used in data center data Warehouse, here mainly refers to the analysis and mining of the data source data warehouse of the audit system through big data technology and data integration means), according to the audit requirements of the whole process of the project, to build a multi-dimensional analysis model across disciplines, business domains, and systems. Data integration, big data analysis and other technologies, cleaning, transformation, and calculation processing form a set of multiple business scenarios for auditing operations. Among them, the business model of auditing is cross-system and cross-professional, and there are many corresponding sources. Data cleaning and transformation through ETL , The loading processing method can put the data in the audit data mart, support multiple business audit scenarios, and realize the automatic detection and early warning of the whole process of the project through the visualization of the early warning monitoring model and the scanning of project risk opinions, which solves the problem of data integration. It solves the dilemma of short model life cycle caused by business changes, and solves the problem of business breakpoints. It realizes the sharing and integration of data resources; promotes the transformation of audit work methods, meets the needs of full, dynamic, and online audits, ensures independence and objectivity, and improves the company's internal audit competence. Specifically, the multi-dimensional analysis model includes a doubt model and an inspection model, wherein the analysis model is constructed by: taking the audit guide as a blueprint, combining with the list of audit issues over the years, and in accordance with the current laws, regulations and rules, the business data, For risk points, design audit business models for suspicious points and inspections, and conduct cross-system and cross-professional analysis and verification of number-taking rules and logic design. After the model is constructed, the data is processed to form a result set through technical means such as ETL and big data. Support audit model application. After the auditors find suspicious problems through the application, they confirm the suspicious problems by verifying and confirming with the audited unit.

Through the technical scheme of the present application, the detailed process of realizing the objective improvement effect is as follows:

The first is to sort out the list of data concerned by various project audit online, and through the system to automatically retrieve and query whether the project data of more concern exists in the system, to realize the automatic comparison of pre-trial attention data online, which is convenient for auditors to evaluate the line before the audit. To further determine the feasibility of conducting online audits;

Second, the early warning system of this application is set with a solidified doubt model. In order to solve the problem of poor project auditing pertinence and orientation, the early warning system of this application automatically reminds the risk doubts at each stage of the project to help auditors trace the risk data of each stage of the project. , quickly locate problems and doubts, and achieve full coverage, multi-dimensional, and whole-process continuous tracking audit of massive engineering data with low investment;

The third is the engineering project data in terms of investment project approval, survey and design, budget (budget) management, bidding, contract management, equipment and material management audit, project management, completion acceptance, project settlement, financial management, final settlement, post-evaluation, etc. 12 The data can be classified and displayed at each stage, and the data can be penetrated to the details layer by layer to realize the traceability of the data; in order to facilitate the auditors to grasp the data of each stage, and quickly understand the doubtful risk problems of each stage, the system provides the whole process data to the multi-dimensional doubtful point model. The retrieval and switching of data is convenient for auditors to grasp the doubts and risks in the relevant stages, so as to quickly discover and locate the doubtful risks or problems, with convenient operation and strong practicability;

The fourth is to set rules or thresholds for the risk points that the audit focuses on, the system polls and monitors periodically, builds and forms an audit analysis and monitoring model, provides visual reminders, improves project audit analysis and monitoring capabilities, and meets the needs of daily supervision and in-process auditing. .

Fifth, according to the project audit report template, set the rules and logic of automatic number acquisition, generate dynamic templates, and generate audit reports with one click. The system automatically captures data and writes it into the report template to form project approval, construction scale, construction process, commissioning, and capital. , transfer and other project overview information, and use the doubt model to sort out the corresponding audit issues and policy basis, capture the doubt results for the problems in the analyzed projects, and apply the corresponding audit issues, policy basis and other content, and based on the sorted out various questions to form an audit opinion.

The technical key points or keywords of this application are explained as follows:

1. Efficient data processing: Based on the audit guidelines, combined with the list of audit issues over the years, and in accordance with the current laws, regulations and rules, build the business logic and data retrieval rules of the audit business scenario, combine the audit data mart data model, and use ETL and other data Processing tools, through the process of cleaning, transformation, aggregation, parallel computing, streaming computing and other processes, the integrated data center of the whole business unified data center or the source historical layer data processing and storage to the audit data mart, to achieve timing automatic processing, the results are automatically recorded .

2. Multi-dimensional data analysis technology: For big data analysis technology, including data mining and machine learning technologies; realize custom query of multi-dimensional data such as item-level and data-item-level, according to the frequency of data usage, realize homepage recommendation for commonly used retrieval, improve System convenience; realize multi-dimensional analysis, carry out risk prediction, provide intuitive, efficient and high-value data to users, and improve intelligent analysis and auxiliary decision-making capabilities.

Now in conjunction with Fig. 2 to Fig. 4, the automatic detection and early warning method of project whole process risk of the present invention is described in detail, including the following steps:

(1) Trigger the risk automatic detection and early warning technology of the whole process of the project

The basic information of the project triggers the automatic detection and early warning of risks in the whole process of the project. First, the big data processing and analysis are carried out according to the whole process of the project audit business and the data retrieval logic. Through visual display, automatic risk detection and early warning in the whole process of the project can be realized.

(2) Scanning detection based on "MPP + big data" technology

After the automatic risk detection and warning of the whole process of the project is triggered, the automatic risk detection and warning function of the whole process of the project is called. The number of models. Specifically, use the "select" statement to query "project_code" in "sj_gg_yjsm" to determine whether the project has been scanned for risks. If it has been scanned, the data will be updated iteratively. If not, the data will be processed and analyzed according to the scanning rules and big data. The method of global risk scanning suspicious point model, and then use the "insert" statement to insert suspicious point data in batches, and finally form a visual audit suspicious point.

(3) Visual display of suspicious points

The suspicious data of the project is captured from the database through ajax, assembled into a json string, and returned to the front desk, in the form: [{"step_code":"QGC_00101","step_name":"investment approval","risk_num":15}] . The front-end analyzes the string, controls the display style through css, and combines with the jquery rendering interface to form a suspicious point module and displays the suspicious point data list and the number of suspicious points, and adds a penetration function to the suspicious point model, which can be traced again.

Compared with the prior art, the solution of the present application has at least one of the following advantages:

Under normal circumstances, audit work mainly relies on a single business system for data integration and analysis, and requires offline verification of paper documents, which consumes a lot of audit human resources, and it is difficult to improve the efficiency of audit work.

The automatic risk detection and early warning technology for the whole process of the project is different from the previous audit work. By sorting out the focus indicators and risk detection points in the project process, it helps auditors to trace the risk data of each stage of the project, quickly locate the problems and doubts, improve the efficiency of audit work, save audit costs, reduce Audit risks, improve resource utilization, and give full play to the audit function. At the same time, the automatic risk detection and early warning technology in the whole process of the project has broken through the barriers between businesses, realized cross-business data analysis and mining, and improved the level of data-based auditing.

As shown in FIG. 5 , the present invention also proposes an automatic risk detection and early warning system for the whole process of the project, wherein, the automatic detection and early warning system for the whole process risk of the project includes: a data analysis and mining module 10, an establishment of a doubt analysis module 20, and acquisition of doubts. Module 30 and visualization module 40, wherein, the data analysis and mining module 10 is used for data analysis and mining of enterprise-level full-service data sets; the establishment of a doubt analysis module 20 is used to establish a doubt analysis model according to the audit business scenario; the acquisition module 30 is used to scan the mined data based on the doubt analysis model to obtain doubts; and the visualization module 40 is used to visualize the obtained doubts to provide decision-making information for decision-making departments.

FIG. 6 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in FIG. 6 , the terminal device 6 in this embodiment includes: a processor 60 , a memory 61 and a computer program 62 stored in the memory 61 and running on the processor 60 , such as an automatic risk detection and early warning program in the entire project process. When the processor 60 executes the computer program 62, it implements the steps in the above-mentioned embodiments of the whole-process risk automatic detection and early warning method for each item, for example, the above-mentioned steps S1 to S4. Alternatively, when the processor 60 executes the computer program 62, the functions of the modules/units in the above device embodiments, for example, the functions of the modules 10 to 40 shown in FIG. 3 are implemented.

Exemplarily, the computer program 62 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 61 and executed by the processor 60 to accomplish the present invention. One or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 62 in the terminal device 6 .

The terminal device 6 may be a computing device such as a desktop computer, a notebook computer, a palmtop computer, and a cloud server. The terminal device 6 may include, but is not limited to, a processor 60 and a memory 61 . Those skilled in the art can understand that FIG. 3 is only an example of the terminal device 6, and does not constitute a limitation on the terminal device 6, and may include more or less components than the one shown, or combine some components, or different components, For example, the terminal device may further include an input and output device, a network access device, a bus, and the like.

The so-called processor 60 may be a central processing unit (Central Processing Unit, CPU), and may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 61 may be an internal storage unit of the terminal device 6 , such as a hard disk or a memory of the terminal device 6 . The memory 61 may also be an external storage device of the terminal device 6, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash memory card (Flash card) equipped on the terminal device 6. Card), etc. Further, the memory 61 may also include both an internal storage unit of the terminal device 6 and an external storage device. The memory 61 is used to store computer programs and other programs and data required by the terminal device 6 . The memory 61 can also be used to temporarily store data that has been output or is to be output.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit, and the above-mentioned integrated units may adopt hardware. It can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above-mentioned system, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of the present invention.

In the embodiments provided by the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, 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. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated modules/units, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments, and can also be completed by instructing relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the program is executed by the processor, the steps of the foregoing method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory) , Random Access Memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable media may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer-readable media Electric carrier signals and telecommunication signals are not included.

Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples; under the spirit of the present invention, the above embodiments or There may also be combinations between technical features in different embodiments, steps may be carried out in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.

Additionally, well known power/ground connections to integrated circuit (IC) chips and other components may or may not be shown in the figures provided in order to simplify illustration and discussion, and in order not to obscure the present invention. . Furthermore, devices may be shown in block diagram form in order to avoid obscuring the present invention, and this also takes into account the fact that the details regarding the implementation of these block diagram devices are highly dependent on the platform on which the invention will be implemented (i.e. , these details should be fully within the understanding of those skilled in the art). Where specific details (eg, circuits) are set forth to describe exemplary embodiments of the invention, it will be apparent to those skilled in the art that these specific details may be used without or with changes The present invention is carried out below. Accordingly, these descriptions are to be considered illustrative rather than restrictive.

Although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations to these embodiments will be apparent to those of ordinary skill in the art from the foregoing description. For example, other memory architectures (eg, dynamic RAM (DRAM)) may use the discussed embodiments.

In the technical solution implemented by the present invention, the designed deep convolutional neural network model is used to first extract features from the dashboard information in natural scenes, and then perform digital identification, pointer positioning, and reading judgment according to the extracted information. On the basis of comparing and combining the previous design of pointer-type instrument identification, this solution solves the problem of difficulty in extracting instrument panel information in natural scenes on the one hand, and solves the problem of slanted number recognition on the instrument panel on the other hand. A scheme with high generalization, strong robustness and good generality.

As will be appreciated by those skilled in the art, the present invention includes apparatuses for performing one or more of the operations described in this application. These devices may be specially designed and manufactured for the required purposes, or they may include those known in general purpose computers. These devices have computer programs stored in them that are selectively activated or reconfigured. Such a computer program may be stored in a device (eg, computer) readable medium including, but not limited to, any type of medium suitable for storing electronic instructions and coupled to a bus, respectively Types of disks (including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks), ROM (Read-Only Memory, read-only memory), RAM (Random Access Memory, random access memory), EPROM (Erasable Programmable Read-Only Memory, Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory, Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or optical card. That is, a readable medium includes any medium that stores or transmits information in a form that can be read by a device (eg, a computer). Those skilled in the art will understand that computer program instructions can be used to implement each block of these structural diagrams and/or block diagrams and/or flow diagrams, and combinations of blocks in these structural diagrams and/or block diagrams and/or flow diagrams . Those skilled in the art can understand that these computer program instructions can be provided to a general-purpose computer, a professional computer or a processor of other programmable data processing methods to implement, so that the present invention can be executed by a processor of a computer or other programmable data processing method. The block or blocks specified in the block or blocks of the block diagrams and/or block diagrams and/or flow diagrams of the invention are disclosed.

Those skilled in the art can understand that the various operations, methods, steps, measures, and solutions discussed in the present invention may be alternated, modified, combined or deleted. Further, other steps, measures, and solutions in the various operations, methods, and processes that have been discussed in the present invention may also be alternated, modified, rearranged, decomposed, combined, or deleted. Further, steps, measures and solutions in the prior art with various operations, methods, and processes disclosed in the present invention may also be alternated, modified, rearranged, decomposed, combined or deleted. It should be understood by those of ordinary skill in the art that the discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples; under the spirit of the present invention, the above embodiments or There may also be combinations between technical features in different embodiments, steps may be carried out in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (9)

1. a project whole process risk automatic detection and early warning method is characterized in that, described project whole process risk automatic detection and early warning method comprises: S1: Data analysis and mining of enterprise-level full-service data sets; S2: According to the audit business scenario, establish a doubt analysis model; S3: Scan the mined data based on the doubt analysis model to obtain doubts; S4: Visually display the obtained doubts to provide decision-making information for decision-making departments. 2. The method for automatic detection and early warning of project whole process risk as claimed in claim 1, characterized in that, in step S1, relying on the enterprise-level full-service unified data center, based on the MPP big data technology framework, to form the enterprise-level full-service unified data center. business dataset. 3. The method for automatic detection and early warning of project whole process risk as claimed in claim 1, characterized in that, in step S2, through big data technology, the enterprise-level full-service data set is cleaned, converted, calculated and processed to form audit operations multi-service set of scenes. 4. The method for automatic detection and early warning of risks in the whole process of a project as claimed in claim 3, wherein the step S2 comprises: constructing a multi-dimensional doubt analysis model that is cross-professional, cross-business, and cross-system according to the audit requirements of the whole process of the project . 5. The method for automatic detection and early warning of risk in the whole project process as claimed in claim 3, wherein the step S3 comprises: based on the doubt analysis model, the data after mining and the attention index and risk detection in the whole process of the project are detected Point to compare to get doubts. 6. A project whole process risk automatic detection and early warning system is characterized in that, comprising: The data analysis and mining module is used for data analysis and mining of enterprise-level full-service data sets; Establish a doubt analysis module, which is used to establish a doubt analysis model according to the audit business scenario; an acquisition module for suspicious points, which is used to scan the mined data based on the suspicious point analysis model to acquire suspicious points; The visualization module is used to visualize the acquired doubts to provide decision-making information for decision-making departments. 7 . The automatic risk detection and early warning system for the whole process of a project according to claim 6 , wherein the enterprise-level full-service data set is formed by relying on the enterprise-level full-service unified data center and based on the MPP big data technology architecture. 8 . 8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the computer program as claimed in the claims The steps of the automatic detection and early warning method for the whole process risk of the project described in any one of 1 to 5. 9. A computer-readable storage medium, wherein the computer-readable storage medium is stored with a computer program, characterized in that, when the computer program is executed by a processor, the project as claimed in any one of claims 1 to 5 is realized. The steps of the process risk automatic detection and early warning method.

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