Data management method and system based on survey information

Abstract

The invention discloses a data management method and system based on survey information, and relates to the technical field of survey data management.The system comprises a data sequence management module, a data risk analysis module and a data management adjustment module, and the data sequence management module, the data risk analysis module and the data management adjustment module are arranged. Various survey data of a survey site can be regularly and orderly managed, risk analysis is preferentially carried out on the survey data to be managed, deep risk analysis is carried out on each kind of survey data from two risk levels of data defect risk and data abnormal risk, and when the survey risk data appear, the risk analysis is carried out on each kind of survey data. The survey personnel can take corresponding measures in time, synchronously adjust the analysis sequence of the subsequent survey data, and preferentially analyze the survey data with high linkage degree with the survey risk data.

Description

Technical Field

[0001] The present invention relates to the technical field of survey data management, and more specifically, to a data management method and system based on survey information. Background Art

[0002] Survey information refers to various survey data, survey materials, and survey images obtained through various means and methods during the survey process, including the geographical environment, natural resources, and engineering construction of the survey site. Among them, survey data can reflect the actual situation of the survey site in the most direct, complete, and accurate way. Survey data is not only large and complex, but its accuracy and completeness are directly related to the scientific nature of subsequent decision-making and the feasibility of engineering. In the field of survey technology, with the advancement of science and technology and the complexity of engineering construction, the collection, processing, and management of survey data have become increasingly important.

[0003] However, traditional survey data management methods face many challenges. First, survey data often lack unified management standards and processes, resulting in chaotic data storage, difficult query, and difficulty in effective use. Second, the risk management of survey data is insufficient, and there is a lack of timely identification and early warning mechanisms for possible data defects and data anomalies, which increases the risk of data use. In addition, the management of survey data often lacks flexibility and cannot be dynamically adjusted according to the importance and urgency of the data, resulting in inefficient management.

[0004] In order to solve the above problems, the present invention proposes a data management method and system based on survey information. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention aims to provide a data management method and system based on survey information.

[0006] To achieve the above object, the present invention provides the following technical solutions: A data management system based on survey information, including a data sequence management module, a data risk analysis module, and a data management adjustment module; The data sequence management module is used to determine the survey site and set the data management time to , after each data management period, a data management sequence is generated, and the survey risk values ​​of various survey data are obtained in sequence according to the data management sequence; The data risk analysis module obtains a survey risk value of each survey data, and determines whether it is necessary to change the data management order to a risk data management order based on the comparison result between the survey risk value and the survey risk boundary value; The data management adjustment module generates a survey management value when acquiring the survey risk value of various survey data, and determines whether to adjust the data management duration based on the comparison result between the survey management value and the survey management threshold.

[0007] Furthermore, the data management order is generated as follows: the survey critical management values ​​of various survey data are obtained, the various survey data are sorted in descending order according to the values ​​of the survey critical management values, and the data management order is generated according to the sorting order.

[0008] Furthermore, the method for obtaining the survey critical management value of the survey data is as follows: obtain the survey risk value corresponding to m consecutive data management time periods of a type of survey data before the current time, sort all the survey risk values ​​in the order of acquisition, sum and average the two adjacent survey risk values ​​after sorting to obtain the median of the survey continuous risk, sum and average all the medians of the survey continuous risks to obtain the survey critical management value of the survey data.

[0009] Furthermore, the survey risk value of the survey data is obtained as follows: collect real data of a survey data within the data management period, extract data features from the real data, obtain the real survey features, obtain the data defect risk analysis model and the data anomaly risk analysis model corresponding to the survey data, input the real survey features into the data defect risk analysis model and the data anomaly risk analysis model respectively, and output the data defect risk value Dekt and the data anomaly risk value Ervb, and use the formula The survey risk value Vsgh of the survey data is obtained, where da is the data defect risk coefficient and db is the data anomaly risk coefficient.

[0010] Furthermore, based on the comparison result between the survey risk value and the survey risk threshold value, determine whether it is necessary to change the data management order to the risk number management order, specifically: set the survey risk threshold value, when the survey risk value of the survey data is greater than or equal to the survey risk threshold value, mark the survey data as survey risk data, and synchronously generate the risk number management order, and obtain the survey risk values ​​of various survey data in turn according to the risk number management order; when the survey risk value of the survey data is less than the survey risk threshold value, continue to obtain the survey risk value of the next survey data in the data management order.

[0011] Furthermore, the risk number management sequence is generated as follows: all survey data after the survey risk data in the risk number management sequence are marked as survey linkage data, survey linkage values ​​of various survey linkage data are obtained, various survey linkage data are sorted in order from small to large according to the values ​​of the survey linkage values, and the risk number management sequence is generated according to the sorting.

[0012] Furthermore, the survey linkage value of the survey linkage data is obtained as follows: obtain the risk gradient value of the survey risk data and the risk gradient value of the survey linkage data, perform difference calculation on the risk gradient value of the survey risk data and the risk gradient value of the survey linkage data and take the absolute value to obtain the survey linkage value of the survey linkage data.

[0013] Further, the risk gradient value is obtained in the following manner: obtain a survey risk value corresponding to n consecutive data management periods of survey data before the current time, obtain a comprehensive management risk value for each data management period, compare all comprehensive management risk values ​​in pairs, obtain risk comparison values ​​of the two compared comprehensive management risk values, sum all risk comparison values, and obtain a risk gradient value; The comprehensive management risk value of the data management duration is obtained as follows: the survey risk value is calculated by ratio with the corresponding data management duration to obtain the comprehensive management risk value of the data management duration; Obtain the risk comparison value of the two compared comprehensive management risk values, specifically: sum the two compared comprehensive management risk values ​​to obtain the management risk combined value Tg, calculate the difference between the two compared comprehensive management risk values ​​and take the absolute value to obtain the management risk difference value Bd, and use the formula Obtain the risk comparison value Fxd of the two comprehensive management risk values ​​for comparison.

[0014] Further, based on the comparison result between the survey management value and the survey management threshold, it is determined whether to adjust the data management duration. Specifically, the survey management threshold is set. When the survey management value is greater than the survey management threshold, the survey management threshold is calculated by ratio with the survey management value to obtain the survey management intervention value bv. The data management duration is adjusted to , when the survey management value is less than or equal to the survey management threshold, no processing is performed; The survey management value is generated as follows: the survey risk values ​​of various survey data are summed and averaged to obtain the survey management value.

[0015] Furthermore, a data management method based on survey information includes the following steps: Step 1: Determine the survey site and set the data management time , after each data management period, a data management sequence is generated; Step 2: Obtain the survey risk values ​​of various survey data in sequence according to the data management order; Step 3: Obtain a survey risk value for each type of survey data, and determine whether the data management order needs to be changed to a risk data management order based on the comparison result between the survey risk value and the survey risk cutoff value; Step 4: When the survey risk values ​​of various survey data are obtained, a survey management value is generated, and based on the comparison result between the survey management value and the survey management threshold, it is determined whether to adjust the data management time.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The method of the present invention can manage various survey data at the survey site regularly and orderly, ensuring that the system no longer needs to perform risk analysis on a large amount of survey data at the same time, thereby improving the management efficiency and accuracy of the survey data; 2. Set up data sequence management module, data risk analysis module and data management adjustment module, give priority to risk analysis of survey data that are urgently managed, and conduct in-depth risk analysis on each type of survey data from two risk levels: data defect risk and data anomaly risk. When survey risk data appears, survey personnel can take corresponding measures in a timely manner and simultaneously adjust the analysis sequence of subsequent survey data, give priority to analyzing survey data that has a high degree of linkage with survey risk data, and dynamically adjust the management strategy of survey data based on the analysis results of all survey data at the survey site. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A method flow chart of a data management method based on survey information; Figure 2 It is a system module diagram of a data management system based on survey information. DETAILED DESCRIPTION

[0018] Example 1: Reference Figure 1 , a data management method based on survey information, comprising the following steps: Step 1: Determine the survey site and set the data management time , after each data management period, a data management sequence is generated.

[0019] Step 2: Obtain the survey risk values ​​of various survey data in sequence according to the data management order.

[0020] Step 3: Obtain a survey risk value for each type of survey data, and based on the comparison result between the survey risk value and the survey risk cutoff value, determine whether the data management order needs to be changed to the risk data management order.

[0021] Step 4: When the survey risk values ​​of various survey data are obtained, a survey management value is generated, and based on the comparison result between the survey management value and the survey management threshold, it is determined whether to adjust the data management time.

[0022] The above method can manage various survey data at the survey site regularly and orderly, ensuring that the system no longer needs to perform risk analysis on a large amount of survey data at the same time, thereby improving the management efficiency and accuracy of the survey data.

[0023] Example 2: Reference Figure 2 , a data management system based on survey information, including a data sequence management module, a data risk analysis module, and a data management adjustment module.

[0024] Survey information refers to various survey data, survey information, and survey images about the geographical environment, natural resources, engineering construction, etc. of the survey site obtained through various means and methods during the survey process. Among them, survey data can reflect the actual situation of the survey site in the most direct, complete, and accurate way.

[0025] Data sequence management module: determine the survey site and set the data management time (During the operation of the data management system, the data management time is infinitely looped). After each data management time, a data management sequence is generated, and the survey risk values ​​of various survey data are obtained in sequence according to the data management sequence.

[0026] The method for obtaining the survey risk value of survey data is as follows: collect real data of a type of survey data within the data management period, extract data features from the real data (data feature extraction methods include data dimensionality reduction, etc.), obtain the real survey features, obtain the data defect risk analysis model and the data anomaly risk analysis model corresponding to the survey data, input the real survey features into the data defect risk analysis model and the data anomaly risk analysis model respectively, and output the data defect risk value Dekt and the data anomaly risk value Ervb, and use the formula The survey risk value Vsgh of this type of survey data is obtained, where da is the data defect risk coefficient, db is the data anomaly risk coefficient, the value of da is 0.82, and the value of db is 0.79.

[0027] The data management order is generated as follows: obtain the survey critical management values ​​of various survey data (survey data include stratigraphic data, geological structure data, topographic data, surface cover data, water quality data, etc., and each type of survey data is collected and obtained through corresponding survey equipment), sort the various survey data in descending order according to the values ​​of the survey critical management values, and generate the data management order according to the sorting order.

[0028] The method for obtaining the survey critical management value of survey data is as follows: obtain the survey risk value corresponding to m consecutive data management time periods of survey data before the current time, sort all the survey risk values ​​in the order of acquisition, sum and average the two adjacent survey risk values ​​after sorting, and obtain the median of the survey continuous risk, sum and average all the median of the survey continuous risk, and obtain the survey critical management value.

[0029] Each type of survey data corresponds to a data defect risk analysis model and a data anomaly risk analysis model. In this embodiment, the construction process of the data defect risk analysis model and the data anomaly risk analysis model of the formation data will be disclosed as an example.

[0030] The process of constructing the data defect risk analysis model for stratigraphic data is as follows: collect the real survey characteristics of i stratigraphic data, build a neural network model, use the real survey characteristics of the stratigraphic data as the training data of the neural network model, assign a data defect risk value to each training data, and the range of the data defect risk value is (1.0~4.0). The larger the data defect risk value, the more serious the data defects in the stratigraphic data (data defects can be missing data integrity, data accuracy deviation, etc.), and the smaller the data defect risk value, the milder the data defects in the stratigraphic data. The training data is divided into a training set and a validation set according to a set ratio of 3:1, and the neural network is iteratively trained on the training set and the validation set. After the training is completed, the data defect risk analysis model for stratigraphic data is constructed.

[0031] The process of constructing the data anomaly risk analysis model for stratigraphic data is as follows: collect the real survey characteristics of j stratigraphic data, build a neural network model, use the real survey characteristics of the stratigraphic data as the training data of the neural network model, assign a data anomaly risk value to each training data, and the range of the data anomaly risk value is (2.0~6.0). The larger the data anomaly risk value, the more abnormal the stratigraphic data is (the geological processes such as the fractures, folds, and magmatic activities in the bottom layer will cause the stratigraphic data to be more abnormal). The smaller the data anomaly risk value, the more normal the stratigraphic data is. The training data is divided into a training set and a validation set according to a set ratio of 4:1, and the neural network is iteratively trained on the training set and the validation set. After the training is completed, the data anomaly risk analysis model for stratigraphic data is constructed.

[0032] Data risk analysis module: each time a survey risk value of a survey data is obtained, a survey risk cutoff value is set (the survey risk cutoff value is the preset threshold of the system); when the survey risk value of the survey data is greater than or equal to the survey risk cutoff value, the survey data is marked as survey risk data (after the survey risk data appears, the survey personnel will take corresponding measures); and a risk number management sequence is generated synchronously; the survey risk values ​​of various survey data are obtained in turn according to the risk number management sequence; when the survey risk value of the survey data is less than the survey risk cutoff value, the survey risk value of the next survey data is obtained according to the data management sequence.

[0033] The risk number management sequence is generated as follows: all survey data after the survey risk data in the risk number management sequence are marked as survey linkage data, the survey linkage values ​​of various survey linkage data are obtained, the various survey linkage data are sorted in order from small to large according to the values ​​of the survey linkage values, and the risk number management sequence is generated according to the sorting.

[0034] The method for obtaining the survey linkage value of the survey linkage data is as follows: obtain the risk gradient value of the survey risk data and the risk gradient value of the survey linkage data, perform difference calculation on the risk gradient value of the survey risk data and the risk gradient value of the survey linkage data and take the absolute value to obtain the survey linkage value of the survey linkage data.

[0035] The risk gradient value is obtained as follows: obtain the survey risk value corresponding to n consecutive data management periods of survey data before the current time, obtain the comprehensive management risk value of each data management period, compare all comprehensive management risk values ​​in pairs, obtain the risk comparison value of the two compared comprehensive management risk values, sum all risk comparison values, and obtain the risk gradient value.

[0036] The comprehensive management risk value of the data management duration is obtained as follows: the survey risk value is calculated by ratio with the corresponding data management duration to obtain the comprehensive management risk value of the data management duration.

[0037] Obtain the risk comparison value of the two compared comprehensive management risk values, specifically: sum the two compared comprehensive management risk values ​​to obtain the management risk combined value Tg, calculate the difference between the two compared comprehensive management risk values ​​and take the absolute value to obtain the management risk difference value Bd, and use the formula Obtain the risk comparison value Fxd of the two comprehensive management risk values ​​for comparison.

[0038] Data management adjustment module: When the survey risk value of various survey data is obtained, the survey management value is generated, and the survey management threshold is set (the survey management threshold is the preset threshold of the system). When the survey management value is greater than the survey management threshold, the survey management threshold is calculated by the ratio of the survey management value to the survey management value to obtain the survey management intervention value bv, and the data management duration is adjusted to When the survey management value is less than or equal to the survey management threshold, no processing is performed.

[0039] The survey management value is generated as follows: the survey risk values ​​of various survey data are summed and averaged to obtain the survey management value.

[0040] By setting up a data sequence management module, a data risk analysis module and a data management adjustment module, various survey data at the survey site can be managed regularly and orderly, with risk analysis given priority to survey data that are under urgent management, and in-depth risk analysis of each type of survey data from two risk levels: data defect risk and data anomaly risk. When survey risk data appears, survey personnel can take corresponding measures in a timely manner and simultaneously adjust the analysis sequence of subsequent survey data, giving priority to analyzing survey data that has a high degree of linkage with survey risk data, ensuring that the system no longer needs to perform risk analysis on a large amount of survey data at the same time, thereby improving the management efficiency and accuracy of survey data, and dynamically adjusting the management strategy of survey data based on the analysis results of all survey data at the survey site.

[0041] The above formulas are all dimensionless and numerical calculations are performed, and the preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0042] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0043] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0044] Those of ordinary skill in the art will appreciate 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. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0045] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0046] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0047] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0048] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data management system based on survey information, characterized in that: It includes data sequence management module, data risk analysis module and data management adjustment module; The data sequence management module is used to determine the survey site and set the data management time to , after each data management period, a data management sequence is generated, and the survey risk values ​​of various survey data are obtained in sequence according to the data management sequence; The data risk analysis module obtains a survey risk value of each survey data, and determines whether it is necessary to change the data management order to a risk data management order based on the comparison result between the survey risk value and the survey risk boundary value; The data management adjustment module generates a survey management value when acquiring the survey risk value of various survey data, and determines whether to adjust the data management duration based on the comparison result between the survey management value and the survey management threshold.

2. A data management system based on survey information according to claim 1, characterized in that: The data management sequence is generated as follows: obtain the survey critical management values ​​of various survey data, sort the various survey data in descending order according to the values ​​of the survey critical management values, and generate the data management sequence according to the sorting order.

3. A data management system based on survey information according to claim 2, characterized in that: The method for obtaining the survey critical management value of survey data is as follows: obtain the survey risk value corresponding to m consecutive data management time periods of a type of survey data before the current time, sort all the survey risk values ​​in the order of acquisition, sum and average the two adjacent survey risk values ​​after sorting, and obtain the median of the survey continuous risk, sum and average all the medians of the survey continuous risks, and obtain the survey critical management value of the survey data.

4. A data management system based on survey information according to claim 3, characterized in that: The survey risk value of survey data is obtained as follows: collect real data of a survey data within the data management period, extract data features of the real data, obtain the real survey features, obtain the data defect risk analysis model and the data anomaly risk analysis model corresponding to the survey data, input the real survey features into the data defect risk analysis model and the data anomaly risk analysis model respectively, and output the data defect risk value Dekt and the data anomaly risk value Ervb. The survey risk value Vsgh of the survey data is obtained, where da is the data defect risk coefficient and db is the data anomaly risk coefficient.

5. A data management system based on survey information according to claim 1, characterized in that: Based on the comparison result between the survey risk value and the survey risk cutoff value, determine whether it is necessary to change the data management order to the risk number management order, specifically: set the survey risk cutoff value, when the survey risk value of the survey data is greater than or equal to the survey risk cutoff value, mark the survey data as survey risk data, and synchronously generate the risk number management order, and obtain the survey risk values ​​of various survey data in turn according to the risk number management order; when the survey risk value of the survey data is less than the survey risk cutoff value, continue to obtain the survey risk value of the next type of survey data according to the data management order.

6. A data management system based on survey information according to claim 5, characterized in that: The risk number management sequence is generated as follows: all survey data after the survey risk data in the risk number management sequence are marked as survey linkage data, the survey linkage values ​​of various survey linkage data are obtained, the various survey linkage data are sorted in order from small to large according to the values ​​of the survey linkage values, and the risk number management sequence is generated according to the sorting.

7. A data management system based on survey information according to claim 6, characterized in that: The method for obtaining the survey linkage value of the survey linkage data is as follows: obtain the risk gradient value of the survey risk data and the risk gradient value of the survey linkage data, perform difference calculation on the risk gradient value of the survey risk data and the risk gradient value of the survey linkage data and take the absolute value to obtain the survey linkage value of the survey linkage data.

8. A data management system based on survey information according to claim 7, characterized in that: The risk gradient value is obtained as follows: obtain a survey risk value corresponding to n consecutive data management periods of survey data before the current time, obtain a comprehensive management risk value for each data management period, compare all comprehensive management risk values ​​in pairs, obtain risk comparison values ​​of the two compared comprehensive management risk values, sum all risk comparison values, and obtain a risk gradient value; The comprehensive management risk value of the data management duration is obtained as follows: the survey risk value is calculated by ratio with the corresponding data management duration to obtain the comprehensive management risk value of the data management duration; Obtain the risk comparison value of the two compared comprehensive management risk values, specifically: sum the two compared comprehensive management risk values ​​to obtain the management risk combined value Tg, calculate the difference between the two compared comprehensive management risk values ​​and take the absolute value to obtain the management risk difference value Bd, and use the formula Obtain the risk comparison value Fxd of the two comprehensive management risk values ​​for comparison.

9. A data management system based on survey information according to claim 1, characterized in that: Based on the comparison result between the survey management value and the survey management threshold, determine whether to adjust the data management duration. Specifically, set the survey management threshold. When the survey management value is greater than the survey management threshold, calculate the ratio of the survey management threshold to the survey management value to obtain the survey management intervention value bv. Adjust the data management duration to , when the survey management value is less than or equal to the survey management threshold, no processing is performed; The survey management value is generated as follows: the survey risk values ​​of various survey data are summed and averaged to obtain the survey management value.

10. A data management method based on survey information, applied to the data management system based on survey information as claimed in claim 1, characterized in that: The steps include: Step 1: Determine the survey site and set the data management time , after each data management period, a data management sequence is generated; Step 2: Obtain the survey risk values ​​of various survey data in sequence according to the data management order; Step 3: Obtain a survey risk value for each type of survey data, and determine whether the data management order needs to be changed to a risk data management order based on the comparison result between the survey risk value and the survey risk cutoff value; Step 4: When the survey risk values ​​of various survey data are obtained, a survey management value is generated, and based on the comparison result between the survey management value and the survey management threshold, it is determined whether to adjust the data management time.

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