Data analysis method and system based on multi-source heterogeneous water conservancy data fusion management

Abstract

The application discloses a data analysis method and system based on multi-source heterogeneous water conservancy data fusion management, and belongs to the technical field of data processing; and is used for solving the technical problem that the water conservancy data fusion management in the prior art has poor independent supervision and independent strengthening management effect on the implementation effect of water conservancy supervision in different position regions; the supervision implementation coverage data corresponding to the monitoring effective region of different monitoring points is processed and calculated to digitally represent the supervision implementation coverage state corresponding to the monitoring effective region, and the existing water conservancy supervision scheme of the monitoring effective region is subjected to reliable data processing and calculation to obtain the second risk index influence value corresponding to all second risk indexes in the monitoring effective region, and the supervision defect influence data in different aspects is integrated, calculated, analyzed and managed, so that the independent supervision and independent strengthening management of the water conservancy data fusion management on the implementation effect of water conservancy supervision in different position regions are realized.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data. Background Technology

[0002] Water resources data refers to various types of data and information related to the development, utilization, protection, and prevention of floods and droughts. Water resources data includes, but is not limited to, water resources quantity, water quality, precipitation and evaporation, water conservancy engineering facilities information, floods and droughts, ecological environment, etc.

[0003] Existing data analysis solutions for water conservancy data fusion governance are unable to conduct diverse reliability analyses of existing water conservancy regulatory schemes in different locations and regions, nor can they adaptively implement targeted water conservancy regulatory enhancement schemes for different locations and regions based on diverse regulatory analysis results. As a result, the autonomous supervision and autonomous enhancement management effects of water conservancy data fusion governance on the implementation of water conservancy supervision in different locations and regions are not good. Summary of the Invention

[0004] The purpose of this invention is to provide a data analysis method based on the fusion and governance of multi-source heterogeneous water conservancy data, which can solve the technical problem that the existing solutions for water conservancy data fusion and governance have poor autonomous supervision and autonomous reinforcement management effects for water conservancy supervision in different locations and regions.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] Data analysis methods based on the fusion and governance of multi-source heterogeneous water conservancy data include:

[0007] Obtain the effective monitoring area corresponding to different monitoring points in the existing water conservancy supervision scheme, and statistically analyze all targets within the effective monitoring area, as well as the emission standard data corresponding to different targets;

[0008] The system obtains the set of manageable indicators for the existing water conservancy regulatory scheme corresponding to the effective monitoring area, and obtains the set of productive indicators for all targets corresponding to the effective monitoring area based on the emission standard data corresponding to different targets. The system then performs data analysis through the regulatory coverage identification function and outputs the regulatory implementation coverage value corresponding to the effective monitoring area.

[0009] Based on the regulatory implementation coverage value, dynamic prompts are given on whether all productive indicators within the effective monitoring area can be regulated, and statistics and data processing are performed on all productive indicators that cannot be regulated to obtain the first risk indicator impact value corresponding to all productive indicators that cannot be regulated within the effective monitoring area.

[0010] The monitoring effective area corresponding to the second risk index influence value is obtained by performing data processing and calculation on the monitoring data corresponding to the existing water conservancy supervision scheme of the monitoring effective area.

[0011] The supervision reliability of the monitoring effective area is analyzed by using the first risk index influence value and the second risk index influence value, the supervision reliable state corresponding to different monitoring effective areas is determined, and the water conservancy supervision intensification scheme is implemented according to the analysis of the supervision reliable state.

[0012] Preferably, the expression of the supervision coverage identification function is In the formula, JS is the supervision implementation coverage value; u is the set of all target producible indexes corresponding to the monitoring effective area; and U is the set of all monitorable indexes corresponding to the existing water conservancy supervision scheme of the monitoring effective area.

[0013] Preferably, according to the supervision implementation coverage value of 0, it is prompted that all the producible indexes in the monitoring effective area can be supervised.

[0014] According to the supervision implementation coverage value of 1, it is prompted that part of the producible indexes in the monitoring effective area cannot be supervised.

[0015] Preferably, according to the supervision implementation coverage value of 1, all the producible indexes not in the set of monitorable indexes are counted and marked as the first risk index, and the first risk index influence value ZY corresponding to all the first risk indexes in the monitoring effective area is calculated by using the risk index influence formula In the formula, i is different first risk indexes, i=1, 2, 3, …, n; n is a positive integer; ai is the risk index influence factor corresponding to different first risk indexes; N is the total number of indexes in the set of monitorable indexes corresponding to the monitoring effective area; and A is the sum of the risk index influence factors of all the monitorable indexes in the set of monitorable indexes corresponding to the monitoring effective area.

[0016] Preferably, the monitoring suspension duration corresponding to the existing water conservancy supervision scheme of the monitoring effective area is obtained, and the minimum supervision duration corresponding to different producible indexes in the monitoring effective area is compared with the monitoring suspension duration in sequence.

[0017] If the minimum supervision duration is less than the monitoring suspension duration, the producible index corresponding to the minimum supervision duration is marked as the second risk index.

[0018] On the contrary, the producible index corresponding to the minimum supervision duration is not marked.

[0019] Preferably, all the second risk indexes and the corresponding risk index influence factors are calculated by using the risk index influence formula to obtain the second risk index influence value ZY' corresponding to all the second risk indexes in the monitoring effective area.

[0020] Preferably, when performing the supervision reliability analysis on different monitoring effective areas, all targets in the monitoring effective area are acquired, and a first risk index influence value ZY and a second risk index influence value ZY' of the acquired targets are obtained and processed, and a supervision reliability coefficient JK corresponding to the monitoring effective area is calculated by the formula ; in the formula, m is the total number of all targets in the monitoring effective area; a and β are different error factors, and the value ranges of a and β are both (0, 1), and a + β = 1; B is a supervision reliability standard value.

[0021] Preferably, the supervision reliability coefficient is analyzed, if the supervision reliability coefficient is 0, the monitoring effective area is associated with a normal state of supervision reliability;

[0022] if the supervision reliability coefficient is less than or equal to 1, the monitoring effective area is associated with a mild abnormal state of supervision reliability, and a first water conservancy supervision intensification scheme is implemented on the monitoring effective area;

[0023] if the supervision reliability coefficient is greater than 1, the monitoring effective area is associated with a severe abnormal state of supervision reliability, and a second water conservancy supervision intensification scheme is implemented on the monitoring effective area.

[0024] Preferably, the implementation content of the second water conservancy supervision intensification scheme is more than that of the first water conservancy supervision intensification scheme.

[0025] The data analysis system based on multi-source heterogeneous water conservancy data fusion management includes:

[0026] a water conservancy supervision standard data acquisition module, configured to acquire monitoring effective areas corresponding to different monitoring points in an existing water conservancy supervision scheme, and to count all targets in the monitoring effective areas and emission standard data corresponding to different targets;

[0027] a water conservancy supervision implementation data processing module, configured to acquire a supervision index set corresponding to the existing water conservancy supervision scheme of the monitoring effective area, to acquire a producible index set of all targets in the monitoring effective area according to the emission standard data corresponding to different targets, and to perform data analysis on the monitoring effective area by a supervision coverage identification function and output a supervision implementation coverage value corresponding to the monitoring effective area;

[0028] a water conservancy supervision implementation risk processing module, configured to dynamically prompt whether all producible indexes in the monitoring effective area can be supervised according to the supervision implementation coverage value, to count and process all producible indexes that cannot be supervised, and to obtain a first risk index influence value corresponding to all producible indexes that cannot be supervised in the monitoring effective area; and to process and calculate supervision data corresponding to the existing water conservancy supervision scheme of the monitoring effective area, and to obtain a second risk index influence value corresponding to the monitoring effective area.

[0029] The water conservancy supervision strengthening processing analysis module is used for performing supervision reliability analysis on the corresponding monitoring effective area by using the first risk index influence value and the second risk index influence value, determining the supervision reliable state corresponding to different monitoring effective areas, and implementing a targeted water conservancy supervision strengthening scheme for different monitoring effective areas according to the supervision reliable state obtained through analysis.

[0030] Compared with the prior art, the present application has the following beneficial effects:

[0031] The present application processes and calculates the supervision implementation coverage data corresponding to the monitoring effective area of different monitoring points, digitizes the supervision implementation coverage state corresponding to the monitoring effective area, processes and calculates the supervision reliability of the existing water conservancy supervision scheme of the monitoring effective area, obtains the second risk index influence value corresponding to all second risk indexes in the monitoring effective area, integrates, calculates, analyzes and manages the supervision defect influence data in different aspects, realizes autonomous supervision and autonomous strengthening management of the water conservancy data fusion governance effect of water conservancy supervision implementation in different positions and regions, and improves the diversity and adaptability of data processing and analysis of water conservancy data fusion governance. BRIEF DESCRIPTION OF DRAWINGS

[0032] The present application will be further described below in combination with the drawings.

[0033] Figure 1 The present application is based on the data analysis method of multi-source heterogeneous water conservancy data fusion governance.

[0034] Figure 2 The present application is based on the data analysis system of multi-source heterogeneous water conservancy data fusion governance. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0036] Embodiment 1, as shown in the present application is a data analysis method based on multi-source heterogeneous water conservancy data fusion governance, comprising: Figure 1

[0037] Obtain the monitoring effective area corresponding to different monitoring points in the existing water conservancy supervision scheme, and count all targets in the monitoring effective area and the discharge standard data corresponding to different targets;

[0038] ​The monitoring point can be a water conservancy monitoring station. The monitoring effective area corresponding to the water conservancy monitoring station can be the area between the monitoring point and an upstream monitoring point, or can be determined according to the monitoring point and a preset monitoring radius. The monitoring radius is determined according to the actual application scenario and the specific monitoring equipment. The target is a chemical enterprise producing wastewater. The emission standard data corresponding to different targets can be obtained according to the supervision data of the environmental protection department. The emission standard data includes but is not limited to the total monthly wastewater discharge of the target, and all producible indexes contained in the discharged wastewater. The producible indexes include physical indexes and chemical indexes, and the specific indexes are not limited.

[0039] The set of monitorable indexes of the existing water conservancy supervision scheme corresponding to the monitoring effective area is obtained, and the set of producible indexes of all targets corresponding to the monitoring effective area is obtained according to the emission standard data corresponding to different targets. The supervision implementation coverage value JS corresponding to the monitoring effective area is output by data analysis through the supervision coverage identification function.

[0040] The expression of the supervision coverage identification function is In the formula, u is the set of producible indexes of all targets corresponding to the monitoring effective area, and U is the set of monitorable indexes of the existing water conservancy supervision scheme corresponding to the monitoring effective area.

[0041] The supervision implementation coverage value includes a numerical value of 0 or 1.

[0042] It should be noted that the supervision implementation coverage value is used to process and calculate the supervision implementation coverage data corresponding to the monitoring effective area of different monitoring points, so as to digitally represent the supervision implementation coverage state corresponding to the monitoring effective area.

[0043] According to the supervision implementation coverage value, it is dynamically prompted whether all producible indexes in the monitoring effective area can be supervised, and all producible indexes that cannot be supervised are counted and processed to obtain the first risk index influence value corresponding to all producible indexes that cannot be supervised in the monitoring effective area.

[0044] Specifically, according to the supervision implementation coverage value with a numerical value of 0, it is prompted that all producible indexes in the monitoring effective area can be supervised.

[0045] According to the supervision implementation coverage value with a numerical value of 1, it is prompted that there are some producible indexes in the monitoring effective area that cannot be supervised.

[0046] It can be understood that when there are some producible indexes that cannot be supervised, the supervision defect influence corresponding to the producible indexes that cannot be supervised needs to be further analyzed and evaluated.

[0047] According to the regulatory implementation coverage value of 1, all the producible indexes not in the set of regulatable indexes are counted and marked as the first risk indexes, and the risk index influence formula is used The first risk index influence value ZY corresponding to all the first risk indexes in the monitoring effective area is calculated; in the formula, i is a different first risk index, i = 1, 2, 3, …, n; n is a positive integer, representing the total number of first risk indexes; ai is a risk index influence factor corresponding to a different first risk index, which is used to digitally represent the risk index influence of different first risk indexes, and the specific value can be determined by the working personnel in the field according to the working experience, or can be determined according to the previous water conservancy supervision test data, and the specific value is not limited; N is the total number of indexes in the set of regulatable indexes corresponding to the monitoring effective area; A is the sum of the risk index influence factors corresponding to all the regulatable indexes in the set of regulatable indexes corresponding to the monitoring effective area;

[0048] It should be noted that the first risk index influence value is used to process and calculate the index data corresponding to all the first risk indexes in the monitoring effective area, so as to digitally represent the risk index aspect corresponding to the monitoring effective area.

[0049] The monitoring data corresponding to the existing water conservancy supervision scheme of the monitoring effective area is processed and calculated to obtain the second risk index influence value corresponding to the monitoring effective area;

[0050] Specifically, the monitoring suspension time length corresponding to the existing water conservancy supervision scheme of the monitoring effective area is obtained, and the unit is hour, and the minimum monitoring time length corresponding to different producible indexes in the monitoring effective area is compared and judged with the monitoring suspension time length in turn; the minimum monitoring time length can be determined according to the historical water conservancy public opinion feedback data and the laboratory test data corresponding to different producible indexes;

[0051] If the minimum monitoring time length is less than the monitoring suspension time length, the producible index to which the minimum monitoring time length belongs is marked as the second risk index;

[0052] On the contrary, the producible index to which the minimum monitoring time length belongs is not marked;

[0053] It can be understood that the traditional monitoring means is difficult to capture intermittent and short-time strong discharge behavior, for example, a printing and dyeing plant controls the discharge time in the sampling interval of the monitoring equipment (such as 1-3 am), and the discharge time is less than 30 minutes each time, so that the monitoring data always shows compliance;

[0054] All the second risk indexes and the corresponding risk index influence factors are calculated by the risk index influence formula to obtain the second risk index influence value corresponding to all the second risk indexes in the monitoring effective area and marked as ZY';

[0055] In this embodiment of the invention, by performing data processing and calculation on the existing water conservancy supervision schemes in the effective monitoring area to ensure the reliability of the scheme supervision, the impact values ​​of the second risk indicators corresponding to all second risk indicators in the effective monitoring area are obtained. This not only enables proactive supervision and digital processing of supervision defects from the perspective of existing water conservancy supervision schemes, but also provides reliable data support for supervision defect data for subsequent data processing and analysis of the supervision reliability corresponding to the effective monitoring area.

[0056] When conducting regulatory reliability analysis on different effective monitoring areas, all targets within the effective monitoring area are obtained, along with the impact values ​​ZY of the first risk indicator and ZY′ of the second risk indicator obtained from regulatory processing, and then analyzed using the formula... Calculate the regulatory reliability coefficient JK corresponding to the effective monitoring area; where m is the total number of all targets within the effective monitoring area; α and β are different error factors, and their values ​​are both in the range of (0, 1), α+β=1; B is the regulatory reliability standard value, which can be determined based on the design requirements data corresponding to the existing water conservancy regulatory scheme, or based on the regulatory requirements data corresponding to the effective monitoring area;

[0057] It should be explained that the regulatory reliability coefficient is used to integrate and calculate the regulatory data on defects from different aspects in the early stage, so as to digitally represent the regulatory reliability status of the corresponding effective monitoring area.

[0058] Data analysis of the regulatory reliability coefficient is conducted to determine the regulatory reliability status corresponding to different effective monitoring areas, and targeted water conservancy regulatory enhancement plans are implemented for different effective monitoring areas based on the regulatory reliability status obtained from the analysis.

[0059] If the regulatory reliability coefficient is 0, then the effective monitoring area will be associated with a normal regulatory reliability status.

[0060] If the regulatory reliability coefficient is less than or equal to 1, the effective monitoring area will be associated with a slightly abnormal regulatory reliability state, and the first water conservancy regulatory enhancement plan will be implemented in the effective monitoring area.

[0061] If the regulatory reliability coefficient is greater than 1, the effective monitoring area will be associated with a severe abnormality in regulatory reliability, and a second enhanced water conservancy regulatory scheme will be implemented for the effective monitoring area.

[0062] The second water conservancy supervision enhancement plan has more implementation content than the first water conservancy supervision enhancement plan.

[0063] The first water conservancy supervision enhancement plan could specifically involve deploying a network of miniature spectral sensors (such as SensGuard water quality buoys) to increase tributary monitoring density to 1 km / point; and employing quantum dot fluorescence sensing technology to detect heavy metal ions (such as Pb). 2+, Cd 2 ) ppb level real-time detection;

[0064] The second water conservancy supervision strengthening scheme can be specifically establishing an integrated space-ground monitoring system: satellite remote sensing (such as high-spectral data of Gaofen-5) discovers abnormal color spots → unmanned aerial vehicle multi-spectral imaging locks the pollution source → ground robot sampling verification.

[0065] Different from the prior art, the present application differentiates from different aspects to diversify the processing, supervision reliable state analysis and targeted supervision strengthening management of the existing water conservancy data; in the embodiment of the present application, the risk index aspect and the corresponding supervision defect influence of the existing water conservancy supervision scheme of the monitoring effective area are digitally represented, and the supervision defect influence data of different aspects are integrated, calculated, analyzed and managed, realizing the independent supervision and independent strengthening management of the water conservancy data fusion governance for the implementation effect of water conservancy supervision in different position areas, and improving the diversity and adaptability of data processing analysis of water conservancy data fusion governance.

[0066] In addition, when analyzing the data of the implementation supervision strengthening state of the water conservancy supervision strengthening scheme implemented in different monitoring effective areas, all monitoring effective areas implementing the same water conservancy supervision strengthening scheme, and the total number of first water conservancy abnormalities found by active supervision and the total number of second water conservancy abnormalities found by passive feedback of the same water conservancy supervision strengthening scheme are obtained; passive feedback refers to the water conservancy abnormalities collected by different feedback channels;

[0067] When digitally processing and analyzing the total number of first water conservancy abnormalities and the total number of second water conservancy abnormalities traced back and counted in all monitoring effective areas implementing the same water conservancy supervision strengthening scheme, if M1≠0 and M2=0, a strengthening completely effective label is generated, and the strengthening identifier of the water conservancy supervision strengthening scheme is set to 0; M1 and M2 are respectively the total number of first water conservancy abnormalities and the total number of second water conservancy abnormalities traced back and counted in all monitoring effective areas implementing the same water conservancy supervision strengthening scheme;

[0068] If M1≠0 and M2≠0, a strengthening partially effective label is generated, and the strengthening identifier of the water conservancy supervision strengthening scheme is set to 1;

[0069] If M1=0 and M2≠0, a strengthening partially invalid label is generated, and the strengthening identifier of the water conservancy supervision strengthening scheme is set to 2;

[0070] In addition, the formula is respectively, are the first water conservancy supervision and reinforcement scheme and the second water conservancy supervision and reinforcement scheme; QXk is QX1, QX2, which are the first supervision and reinforcement validity corresponding to the first water conservancy supervision and reinforcement scheme and the second supervision and reinforcement validity corresponding to the second water conservancy supervision and reinforcement scheme; m1k is m11, m12, which are the first total number of water conservancy anomalies found by the first water conservancy supervision and reinforcement scheme and the first total number of water conservancy anomalies found by the second water conservancy supervision and reinforcement scheme; m2k is m21, m22, which are the second total number of water conservancy anomalies found by the passive feedback of the first water conservancy supervision and reinforcement scheme and the second total number of water conservancy anomalies found by the passive feedback of the second water conservancy supervision and reinforcement scheme;

[0071] The supervision and reinforcement validity difference QX0 between the second water conservancy supervision and reinforcement scheme and the first water conservancy supervision and reinforcement scheme is calculated by the formula QX0=QX2-QX1;

[0072] If the supervision and reinforcement validity difference is less than or equal to 0, the reinforcement effect identifier corresponding to the second water conservancy supervision and reinforcement scheme is set to 1;

[0073] On the contrary, the reinforcement effect identifier corresponding to the second water conservancy supervision and reinforcement scheme is set to 0;

[0074] If the reinforcement identifier and the reinforcement effect identifier corresponding to the second water conservancy supervision and reinforcement scheme are both 0, it is prompted that the supervision and reinforcement state of the second water conservancy supervision and reinforcement scheme is normal;

[0075] On the contrary, it is prompted that the supervision and reinforcement state of the second water conservancy supervision and reinforcement scheme is abnormal, and it is prompted to optimize the management of the water conservancy supervision and reinforcement scheme;

[0076] It is worth noting that the embodiments of the present application disclose processing, analyzing and evaluating the implementation effect of the second water conservancy supervision and reinforcement scheme from different aspects, which improves the traceability processing effect after the implementation of the second water conservancy supervision and reinforcement scheme. In addition, based on the technical scheme disclosed in the embodiments of the present application, different abnormal data of the existing water conservancy supervision scheme can be used to analyze the data of the corresponding supervision and reinforcement state of the first water conservancy supervision and reinforcement scheme, and the specific implementation steps are not described here.

[0077] In the embodiments of the present application, the data processing and analysis of the supervision and reinforcement state of the water conservancy supervision and reinforcement scheme implemented in different monitoring effective areas are performed from different aspects, and the water conservancy supervision and reinforcement scheme is optimized and managed according to the analysis result, which realizes further data expansion analysis of water conservancy data fusion processing from the aspect of water conservancy supervision and reinforcement scheme, and further improves the diversity and adaptability of data processing and analysis of water conservancy data fusion management.

[0078] Embodiment 2, as shown in Figure 2 The data analysis system based on the multi-source heterogeneous water conservancy data fusion management includes:

[0079] The water conservancy supervision standard data acquisition module is used for acquiring the monitoring effective area corresponding to different monitoring points in the existing water conservancy supervision scheme, and counting all targets in the monitoring effective area and the discharge standard data corresponding to different targets.

[0080] The water conservancy supervision implementation data processing module is used for acquiring the monitorable index set of the existing water conservancy supervision scheme corresponding to the monitoring effective area, acquiring the producible index set of all targets in the monitoring effective area according to the discharge standard data corresponding to different targets, and performing data analysis through a supervision coverage identification function to output the supervision implementation coverage value corresponding to the monitoring effective area.

[0081] The water conservancy supervision implementation risk processing module is used for dynamically prompting whether all producible indexes in the monitoring effective area can be supervised according to the supervision implementation coverage value, and performing statistics and data processing on all producible indexes that cannot be supervised to obtain the first risk index influence value corresponding to all producible indexes that cannot be supervised in the monitoring effective area.

[0082] The water conservancy supervision strengthening processing analysis module is used for performing supervision reliability analysis on the monitoring effective area by using the first risk index influence value and the second risk index influence value, determining the supervision reliable state corresponding to different monitoring effective areas, and implementing a targeted water conservancy supervision strengthening scheme for different monitoring effective areas according to the supervision reliable state obtained through analysis.

[0083] In several embodiments provided in the present application, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the application are only illustrative, for example, the division of the modules is only a logical function division, and another division mode can be used in actual implementation.

[0084] The modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical modules, which can be located in one place or distributed on multiple network modules. According to actual needs, part or all of the modules can be selected to achieve the purpose of the present embodiment scheme.

[0085] In addition, each function module in each embodiment of the present application can be integrated in one processing module, or each module can exist physically separately, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of hardware plus software function module.

[0086] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be realized in other specific forms without departing from the essential characteristics of the present application.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data, characterized in that, include: Obtain the effective monitoring area corresponding to different monitoring points in the existing water conservancy supervision scheme, and statistically analyze all targets within the effective monitoring area, as well as the emission standard data corresponding to different targets; The system obtains the set of manageable indicators for the existing water conservancy regulatory scheme corresponding to the effective monitoring area, and obtains the set of productive indicators for all targets corresponding to the effective monitoring area based on the emission standard data corresponding to different targets. The system then performs data analysis through the regulatory coverage identification function and outputs the regulatory implementation coverage value corresponding to the effective monitoring area. Based on the regulatory implementation coverage value, dynamic prompts are made on whether all productive indicators within the effective monitoring area can be regulated, and statistics and data processing are performed on all productive indicators that cannot be regulated to obtain the first risk indicator impact value corresponding to all productive indicators that cannot be regulated within the effective monitoring area; productive indicators include physical indicators and chemical indicators. Data processing and calculation are performed on the regulatory data corresponding to the existing water conservancy regulatory scheme in the effective monitoring area to obtain the impact value of the second risk indicator corresponding to the effective monitoring area; Among them, the duration of regulatory suspension corresponding to the existing water conservancy regulatory scheme in the effective monitoring area is obtained, and the minimum duration of regulatory suspension corresponding to different productive indicators in the effective monitoring area is compared with the duration of regulatory suspension in turn. If the minimum regulatory duration is less than the regulatory suspension duration, the productive indicator to which the minimum regulatory duration belongs is marked as the second risk indicator. Conversely, the productive indicators corresponding to the minimum regulatory duration will not be marked. All secondary risk indicators and their corresponding risk indicator impact factors are calculated using the risk indicator impact formula to obtain the impact value of all secondary risk indicators within the effective monitoring area and marked as ZY´. The impact values ​​of the first and second risk indicators are used to conduct regulatory reliability analysis on the effective monitoring areas, determine the regulatory reliability status of different effective monitoring areas, and implement targeted water conservancy regulatory enhancement plans for different effective monitoring areas based on the regulatory reliability status obtained from the analysis.

2. The data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data according to claim 1, characterized in that, The expression for the regulatory coverage identification function is: In the formula, JS is the coverage value of regulatory implementation; u is the set of productive indicators for all targets corresponding to the effective monitoring area; and U is the set of regulatory indicators for the existing water conservancy regulatory scheme corresponding to the effective monitoring area.

3. The data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data according to claim 2, characterized in that, A regulatory coverage value of 0 indicates that all productive indicators within the effective monitoring area can be monitored. The regulatory coverage value of 1 indicates that some productive indicators within the effective monitoring area cannot be regulated.

4. The data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data according to claim 3, characterized in that, Based on the regulatory implementation coverage value of 1, all productive indicators not included in the set of regulated indicators are statistically analyzed and marked as the first risk indicator. The risk indicator impact formula is then used to further analyze these indicators. Calculate the impact value ZY of the first risk indicator corresponding to all first risk indicators within the effective monitoring area; where i represents different first risk indicators, i=1, 2, 3, ..., n; n is a positive integer; ai represents the risk indicator impact factor corresponding to different first risk indicators; N represents the total number of indicators in the set of regulated indicators corresponding to the effective monitoring area; A represents the sum of the risk indicator impact factors corresponding to all regulated indicators in the set of regulated indicators corresponding to the effective monitoring area.

5. The data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data according to claim 4, characterized in that, When conducting regulatory reliability analysis on different effective monitoring areas, all targets within the effective monitoring area are obtained, along with the impact values ​​ZY and ZY´ of the first and second risk indicators obtained from regulatory processing, and then expressed using the formula... Calculate the regulatory reliability coefficient JK corresponding to the effective monitoring area; where m is the total number of all targets within the effective monitoring area; α and β are different error factors, and their values ​​are both in the range of (0, 1), α+β=1; B is the regulatory reliability standard value.

6. The data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data according to claim 5, characterized in that, Data analysis is performed on the regulatory reliability coefficient. If the regulatory reliability coefficient is 0, the effective monitoring area is associated with a normal regulatory reliability status. If the regulatory reliability coefficient is less than or equal to 1, the effective monitoring area will be associated with a slightly abnormal regulatory reliability state, and the first water conservancy regulatory enhancement plan will be implemented in the effective monitoring area. If the regulatory reliability coefficient is greater than 1, the effective monitoring area will be associated with a severely abnormal regulatory reliability state, and a second enhanced water conservancy regulatory scheme will be implemented for the effective monitoring area.

7. The data analysis method for governance based on the fusion of multi-source heterogeneous water conservancy data according to claim 6, characterized in that, The second water conservancy supervision enhancement plan has more implementation content than the first water conservancy supervision enhancement plan.

8. A data analysis system for multi-source heterogeneous water conservancy data fusion and governance, employing the data analysis method for multi-source heterogeneous water conservancy data fusion and governance as described in any one of claims 1-7, characterized in that, include: The water conservancy supervision standard data acquisition module is used to acquire the effective monitoring area corresponding to different monitoring points in the existing water conservancy supervision scheme, and to count all targets within the effective monitoring area, as well as the emission standard data corresponding to different targets. The water conservancy supervision implementation data processing module is used to obtain the set of monitorable indicators of the existing water conservancy supervision scheme corresponding to the effective monitoring area, and to obtain the set of productive indicators of all targets corresponding to the effective monitoring area based on the emission standard data of different targets. The module also performs data analysis through the supervision coverage identification function and outputs the supervision implementation coverage value corresponding to the effective monitoring area. The water conservancy supervision implementation risk processing module is used to dynamically prompt whether all productive indicators within the effective monitoring area can be supervised based on the supervision implementation coverage value, and to perform statistical and data processing on all productive indicators that cannot be supervised to obtain the first risk indicator impact value corresponding to all productive indicators that cannot be supervised within the effective monitoring area; and to process and calculate the supervision data corresponding to the existing water conservancy supervision plan in the effective monitoring area to obtain the second risk indicator impact value corresponding to the effective monitoring area. The water conservancy supervision enhancement processing and analysis module is used to analyze the supervision reliability of the effective monitoring area by using the influence values ​​of the first risk indicator and the second risk indicator, determine the supervision reliability status of different effective monitoring areas, and implement targeted water conservancy supervision enhancement plans for different effective monitoring areas based on the supervision reliability status obtained from the analysis.

Images