A risk management and control system and device based on GIS information
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DAQING OILFIELD CO LTD
- Filing Date
- 2024-12-06
- Publication Date
- 2026-06-09
Smart Images
Figure CN122175340A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing technology, and specifically to a risk management system and device based on GIS information. Background Technology
[0002] A dual prevention mechanism—risk classification and control, and hazard identification and mitigation—plays a crucial role in the safety management of oilfield operations. However, current risk control measures, once established, are often fixed and lack dynamic adjustment mechanisms. Furthermore, risk management systems suffer from technical deficiencies that may impact the safety and efficiency of oilfield operations. Current risk management often focuses on assessing current risks while neglecting the comprehensive analysis of historical data and potential future risks. This short-sighted approach may lead to the overlooking of certain long-term or complex risks. In practice, rectification requirements for different levels of hazards may not be fully implemented, or there may be a lack of effective linkage between rectification progress and risk control measures, resulting in insufficient effectiveness of risk management. The technical support of risk management systems may be insufficient to handle large amounts of data and complex analytical tasks, limiting the efficiency and accuracy of risk assessment and hazard identification. Summary of the Invention
[0003] This invention provides a risk management system and device based on GIS information to solve existing problems.
[0004] The present invention provides a risk management system and device based on GIS information, which adopts the following technical solution:
[0005] One embodiment of the present invention provides a risk management system based on GIS information, the system comprising the following modules:
[0006] Data acquisition module: used to obtain the number of Class I hazard sources in each unit area, the risk level of each Class I hazard source, and the risk quantification value of the risk level in the current evaluation report;
[0007] Risk source similarity module: used to obtain the risk point name word vector and risk category word vector of each Class I hazard source in each unit area. Based on the risk point name word vector, risk category word vector and risk level quantification value of each Class I hazard source in each unit area, the risk source similarity between any two Class I hazard sources in any two unit areas is obtained.
[0008] Traffic management cost similarity module: used to obtain the location information of each unit area, and based on the location information of each unit area, obtain the traffic management cost similarity between any two Class I hazard sources in any two unit areas;
[0009] Risk Similarity Module: Used to obtain the risk similarity between any two unit areas based on the similarity of hazard sources and traffic management costs between any two Class I hazard sources within any two unit areas;
[0010] The newly added risk value module is used to obtain the rectification effect and the newly added risk value for each unit area based on all Class I hazard sources, their risk levels, and the number of Class I hazard sources in each unit area in the current evaluation report.
[0011] The Dynamic Risk Management Level Module is used to obtain the dynamic risk indicator value of each unit area based on the rectification results and newly added risk values of each unit area; to obtain the dynamic risk management level of each unit area based on the dynamic risk indicator value of each unit area, the number of unit areas, and the risk similarity between any two unit areas; and to implement risk control based on the dynamic risk management level of each unit area.
[0012] Preferably, the step of obtaining the hazard similarity between any two first-class hazard sources in any two unit areas based on the risk point name word vector, risk category word vector, and risk level quantification value of each first-class hazard source in each unit area includes:
[0013]
[0014] In the formula: This indicates that the a-th Class I hazard source within the j-th unit area is related to the j-th... ′ Within the unit region, the a-th ′ Hazard similarity among Category I hazard sources, UWD j,a UWD represents the word vector of the risk point name of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The risk point name word vector of a Class I hazard source, UWDC j,a UWDC represents the word vector representing the risk category of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The word vectors of the risk categories of the first-class hazard sources, UDL j,a UDL represents the risk quantification value of the risk level of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The risk quantification value of the risk level of a Class I hazard source, c represents the preset fifth constant, || represents removing the absolute value, sigmoid() represents the normalization function, and cos() is the cosine function.
[0015] Preferably, obtaining the similarity of traffic management costs between any two Class I hazard sources within any two unit areas based on the location information of each unit area includes:
[0016] The location information of each unit area is mapped into GIS information. The road information of the nearest road to the risk point of each Class I hazard source in each unit area is identified in the GIS information. The road width, road tortuosity, and road undulation of the road where the risk point of each Class I hazard source is located in each unit area are obtained.
[0017] The normalized value of the ratio of the product of the road undulation and the road tortuosity of the nearest road to each Class I hazard source within each unit area to the road width is used to obtain the traffic management cost of each Class I hazard source within each unit area.
[0018] Based on the traffic management cost of each Class I hazard source within each unit area, obtain the similarity of traffic management costs between any two Class I hazard sources within any two unit areas.
[0019] Preferably, obtaining the similarity of traffic management costs between any two Class I hazard sources in any two unit areas based on the traffic management cost of each Class I hazard source in each unit area includes:
[0020] Calculate the relationship between the a-th Class I hazard source and the j-th hazard source within the j-th unit area. ′ Within the unit region, the a-th ′ The absolute value of the difference in traffic management costs for each Class I hazard source;
[0021] The difference between the preset sixth constant and the absolute value of the difference is denoted as the difference between the a-th Class I hazard source and the j-th Class II hazard source within the j-th unit area. ′ Within the unit region, the a-th ′ The similarity of traffic management costs among the first-class hazard sources.
[0022] Preferably, obtaining the risk similarity between any two unit areas based on the similarity of hazard sources and the similarity of traffic management costs between any two first-class hazard sources within any two unit areas includes:
[0023] Within the j-th unit area, the a-th Class I hazard source and the j-th ′ Among the similarity of all Class I hazard sources within a given unit area, the j-th hazard source with the highest similarity will be selected. ′ The first type of hazard source within a unit area is denoted as the matched hazard source of the first type of hazard source in the j-th unit area;
[0024] At the jth ′Within the unit region, the a-th ′ Among the similarity between a Class I hazard source and all Class I hazard sources within the j-th unit area, the Class I hazard source within the j-th unit area corresponding to the highest hazard source similarity is denoted as the j-th hazard source. ′ Within the unit region, the a-th ′ Matching hazards for each Class I hazard;
[0025] Based on the j-th unit region and the j-th ′ By analyzing the similarity of each Class I hazard source within a given unit area with its matching hazard source and the similarity of traffic management costs, the risk similarity between any two unit areas can be obtained.
[0026] Preferably, the step of basing the j-th unit region on the j-th unit region... ′ The risk similarity between each Class I hazard source and its matching hazard source within a given unit area is determined by the similarity of hazard sources and traffic management costs, and the risk similarity between any two unit areas is obtained by:
[0027]
[0028] Where: SUD j,j′ Indicates the j-th unit region and the j-th unit region. ′ Risk similarity of individual unit regions, NI j SR represents the number of Class I hazard sources within the j-th unit area. j ′ ,a,p SD represents the similarity of traffic management costs between the a-th Class I hazard source and its matching hazard source within the j-th unit area. j ′ ,a,p NI represents the hazard similarity between the a-th Class I hazard source and its matching hazard source within the j-th unit area. j′ Indicates the j-th ′ The number of Class I hazard sources within a unit area, SR j " ,a′,p′ Indicates the j-th ′ Within the unit region, the a-th ′ The similarity of traffic management costs between a Class I hazard source and its matching hazard sources, SD j " ,a′,p′ Indicates the j-th ′ Within the unit region, the a-th ′ The similarity of a Class I hazard source to its matching hazard source, where M represents a preset constant.
[0029] Preferably, the step of obtaining the rectification effectiveness and newly added risk value for each unit area based on all Class I hazard sources, their risk levels, and the number of Class I hazard sources in the current evaluation report includes:
[0030] Obtain the risk quantification value of the risk level of each Class I hazard source within each unit area from the previous evaluation report in the current evaluation report;
[0031] The normalized value of the mean of the differences between the risk levels of all Class I hazard sources with the same sequence values in the j-th unit area of the current evaluation report and the previous evaluation report is recorded as the rectification effect of the j-th unit area.
[0032] Compare the Class I hazards in the current evaluation report with those in the previous evaluation report, and compile statistics on the newly added Class I hazards in the current evaluation report;
[0033] The normalized value of the mean risk level of all newly added Class I hazard sources in the j-th unit area is recorded as the newly added risk value of the j-th unit area.
[0034] Preferably, obtaining the dynamic risk indicator value for each unit area based on the rectification results and newly added risk values includes:
[0035] Calculate the sum of the new risk value and the preset fifth constant for each unit area, and record the ratio of the rectification effect of each unit area to the sum as the risk dynamic indicator value of each unit area.
[0036] Preferably, obtaining the dynamic risk management level of each unit area based on the dynamic risk indicator value of each unit area, the number of unit areas, and the risk similarity between any two unit areas includes:
[0037]
[0038] Where: ADL j AD represents the dynamic risk management level of the j-th unit area. j AD represents the dynamic risk index value of the j-th unit area. j′ Indicates the j-th ′ The risk dynamic indicator value for each unit area, SUD j,j′ Indicates the j-th unit region and the j-th unit region. ′ Risk similarity of each unit region, N j This represents the number of unit regions other than the j-th unit region.
[0039] The present invention also proposes a risk management device based on GIS information, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program stored in the memory to implement the steps of the aforementioned module of a risk management system based on GIS information.
[0040] The beneficial effects of the technical solution of this invention are as follows: Addressing the aforementioned background problems, this invention proposes a risk management system and device based on GIS information. This system achieves precise measurement of the risk management status of each unit by quantifying the risk governance progress and newly added risk data within a specific evaluation period. Simultaneously, the system comprehensively considers the similarity of risk sources and geological information among different units, thereby enabling horizontal comparison of management data across multiple units. This method allows the system to assess the dynamic risk management level of each unit and, based on this dynamic risk management level, quantitatively analyze the risk management capabilities and progress of each unit. This process significantly improves the response speed and timeliness of risk management, ensuring that risk management measures can reflect and respond to changes in actual risks in a timely and accurate manner. Attached Figure Description
[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0042] Figure 1 This is a flowchart of a risk management system based on GIS information according to the present invention.
[0043] Figure 2 This is a flowchart illustrating a risk management process based on GIS information in this embodiment. Detailed Implementation
[0044] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a risk management system and apparatus based on GIS information proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0046] The following description, in conjunction with the accompanying drawings, details a specific solution for a risk management system and device based on GIS information provided by the present invention.
[0047] Please see Figure 1 The diagram illustrates a module flowchart of a risk management system based on GIS information according to an embodiment of the present invention. The system includes the following modules:
[0048] Module 101: Data Acquisition Module.
[0049] Data acquisition module: used to obtain information in the current evaluation report about several Class I hazard sources in each unit area, the risk level of each Class I hazard source, and the risk quantification value of the risk level.
[0050] Using a preset evaluation period as one evaluation cycle, the system obtains the evaluation report for the current evaluation and the previous evaluation. The evaluation results can be obtained from the evaluation report. Here, the preset period is 1 week, which is taken as an example.
[0051] Obtain information on several Class I hazard sources within each unit area, as well as the risk level of each Class I hazard source within that unit area. Risk levels are categorized by severity as major risk, significant risk, moderate risk, and low risk.
[0052] This embodiment classifies Class I hazard sources into four levels, from highest to lowest, based on the severity of the safety hazard: major safety hazard, significant safety hazard, general safety hazard, and minor safety hazard. The severity of the safety hazard is determined according to industry-specific standards for assessing major safety hazards related to hazardous chemicals, fire safety, and special equipment.
[0053] In this embodiment, each risk level is quantified. Specifically, the risk quantification value of major risk is a preset first constant, the risk quantification value of relatively large risk is a preset second constant, the risk quantification value of general risk is a preset first constant, the risk quantification value of relatively large risk is a preset third constant, and the risk quantification value of low risk is a preset fourth constant.
[0054] In this embodiment, the preset first constant to the preset fourth constant are 10, 6, 3, and 1, respectively, and this will be used as an example for description.
[0055] Module 102: Risk Source Similarity Module.
[0056] Risk Source Similarity Module: Used to obtain the risk point name word vector and risk category word vector for each Class I hazard source in each unit area. Based on the risk point name word vector, risk category word vector and risk level quantification value of each Class I hazard source in each unit area, the similarity of hazard sources between any two Class I hazard sources in any two unit areas is obtained.
[0057] For the same unit, within the same time period, if the frequency of supervision and inspection is similar, the more hidden dangers found, the worse the unit's management of prevention and control measures for Class I hazard sources is. If the number of larger and more serious hidden dangers found is significantly higher than that of similar units, it further reflects that the unit's dynamic risk management level is low and that the unit does not attach enough importance to the management of prevention and control measures for Class I hazard sources.
[0058] When assessing the dynamic risk management level of various units, the main focus is on evaluating the progress of different units in preventing and controlling risks and hazards. In order to quantify the dynamic risk management level by comparing similar units, it is first necessary to collect various information from each unit to calculate the similarity.
[0059] Obtain the name of the risk point and the corresponding risk category for each Class I hazard source within each unit area. The risk point is the name of the hazardous material in the oilfield extraction process, including hazardous materials such as motors and tanks at various locations. The risk category includes fire, explosion, etc.
[0060] A dictionary of risk point names is constructed using natural language processing methods. Then, one-hot encoding is used to convert these risk point names into word vectors, resulting in word vectors for the risk point names of each Class I hazard source within each unit area. The natural language processing methods and one-hot encoding are well-known techniques, and their specific implementation details are not elaborated in this embodiment.
[0061] The risk categories corresponding to risk points are divided into different words using commas as delimiters. A dictionary is constructed from the words in the risk categories of all risk points using one-hot encoding. The words are then converted into word vectors using the dictionary. The average word vector of all risk categories is calculated as the word vector of the risk category of each first-class hazard source in each unit area.
[0062] Regarding the similarity of risk sources between any two unit areas in the current evaluation report, this embodiment provides a calculation method as follows:
[0063]
[0064] In the formula: This indicates that the a-th Class I hazard source within the j-th unit area is related to the j-th... ′ Within the unit region, the a-th ′ Hazard similarity among Category I hazard sources, UWD j,a UWD represents the word vector of the risk point name of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The risk point name word vector of a Class I hazard source, UWDC j,aUWDC represents the word vector representing the risk category of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The word vectors of the risk categories of the first-class hazard sources, UDL j,a UDL represents the risk quantification value of the risk level of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The risk quantification value of the risk level of a Class I hazard source, c represents the preset fifth constant, || represents removing the absolute value, sigmoid() represents the normalization function, and cos() is the cosine function.
[0065] It should be noted that, in the above formula, since the risk point names are quantized using word vectors through one-hot encoding, when the risk point names are the same, cos(UWD) j,a UWD j′,a′ The value is 1 when the names are different, and 0 when the names are different. Since there may be multiple risk categories, the word vectors are directly converted using a dictionary and the average word vector is calculated. In this case, when the risk categories are not completely the same, cos(UWDC) is used. j,a UWDC j′,a′ ) can also have a certain value, instead of being 0 directly; c takes the value of 1 to avoid the denominator being 0.
[0066] Module 103: Traffic Management Cost Similarity Module.
[0067] Traffic management cost similarity module: used to obtain the location information of each unit area, and based on the location information of each unit area, to obtain the traffic management cost similarity between any two Class I hazard sources in any two unit areas.
[0068] When judging the similarity between different unit areas, it is also necessary to consider the geological conditions of the unit area and the risk management capabilities of the unit area. Different geological information may lead to different costs of handling hidden dangers. Therefore, the hidden danger management between units with more similar geological information in their unit areas is more comparable and has a higher degree of similarity.
[0069] The location information of each unit area is obtained and mapped into GIS information. GIS is a well-known technology, and the specific operation method will not be described in detail in this embodiment.
[0070] All road information is identified in the GIS information and saved using vector data. The road information of the nearest road to each Class I hazard source within each unit area is obtained. The width of the road line is obtained through the GIS information, i.e., the road width. The average slope of the road line is calculated as the tortuosity of each road. The average rate of change of road elevation data is obtained as the road undulation.
[0071] It should be noted that the road information refers to the road information of the vehicle at the time of travel. Road elevation data refers to information describing the height or elevation of the road above the ground. Information such as the slope of each road line can be obtained from GIS data. The average slope of each road line and the average rate of change of each road elevation data can be obtained using the 3DAnalyst tool in ArcToolbox. These tools are well-known technologies, and this example is used here.
[0072] For each Class I hazard source, GIS information is used to extract nearby road information, and the traffic management cost of each Class I hazard source in each unit area is calculated.
[0073] This embodiment provides a calculation method as follows: the ratio of the product of the road undulation and the road tortuosity of the nearest road to each Class I hazard source in each unit area to the road width is linearly normalized using norm() to obtain the traffic management cost of each Class I hazard source in each unit area.
[0074] Furthermore, the similarity of traffic management costs between different risk points in the two unit areas of the current evaluation report is calculated. This embodiment provides one calculation method:
[0075]
[0076] In the formula: This indicates that the a-th Class I hazard source within the j-th unit area is related to the j-th... ′ Within the unit region, the a-th ′ The similarity of traffic management costs among the first-class hazard sources, where K represents a preset sixth constant, and CR j,a CR represents the traffic management cost of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The traffic management cost of a Class I hazard source, where || represents the absolute value.
[0077] It should be noted that the sixth constant is assumed to be 1, taking this as an example.
[0078] Module 104: Risk Similarity Module.
[0079] Risk Similarity Module: This module is used to obtain the risk similarity between any two unit areas based on the similarity of hazard sources and traffic management costs between any two Class I hazard sources within any two unit areas.
[0080] Within a certain period of time, under similar frequency of supervision and inspection, the more hidden dangers discovered, the worse the unit's management of prevention and control measures for Class I hazard sources is. If the number of larger and more serious hidden dangers discovered is significantly higher than that of similar units, it indicates that the unit's dynamic risk management level is low.
[0081] Within the j-th unit area, the a-th Class I hazard source and the j-th ′ Among the similarity of all Class I hazard sources within a given unit area, the j-th hazard source with the highest similarity will be selected. ′ The first type of hazard source within a unit area is denoted as the matched hazard source of the first type of hazard source in the j-th unit area.
[0082] Following the above method, the matched hazard sources for each Class I hazard source within the j-th unit area are obtained.
[0083] At the jth ′ Within the unit region, the a-th ′ Among the similarity between a Class I hazard source and all Class I hazard sources within the j-th unit area, the Class I hazard source within the j-th unit area corresponding to the highest hazard source similarity is denoted as the j-th hazard source. ′ Within the unit region, the a-th ′ Matching hazards for each Class I hazard.
[0084] Following the above method, we obtain the j-th... ′ Matching hazards for each Class I hazard source within a unit area. If multiple maximum hazard sources are similar, one is randomly selected as an example.
[0085] This embodiment provides a method for calculating the risk similarity between two unit regions in the current evaluation report:
[0086]
[0087] Where: SUD j,j′ Indicates the j-th unit region and the j-th unit region. ′ Risk similarity of individual unit regions, NI j SR represents the number of Class I hazard sources within the j-th unit area. j ′ ,a,p SD represents the similarity of traffic management costs between the a-th Class I hazard source and its matching hazard source within the j-th unit area. j ′,a,p NI represents the hazard similarity between the a-th Class I hazard source and its matching hazard source within the j-th unit area. j′ Indicates the j-th ′ The number of Class I hazard sources within a unit area, SR j " ,a′,p′ Indicates the j-th ′ Within the unit region, the a-th ′ The similarity of traffic management costs between a Class I hazard source and its matching hazard sources, SD j " ,a′,p′ Indicates the j-th ′ Within the unit region, the a-th ′ The similarity of a Class I hazard source to its matching hazard source, where M represents a preset constant.
[0088] It should be noted that, since the number of risk sources for the two units may differ and there may be mismatches, it is necessary to calculate the similarity separately for each unit and then take the average. In this embodiment, the preset constant is 2.
[0089] Module 105: Added risk value module.
[0090] The newly added risk value module is used to obtain the rectification effect and newly added risk value for each unit area based on all Class I hazard sources, their risk levels, and the number of Class I hazard sources in each unit area in the current evaluation report.
[0091] After obtaining the similarities between the units, it is also necessary to quantify the recent dynamic hazard source data of each unit. Specifically, the dynamic governance results are quantified by the risk governance achievements and new risks of each unit within a certain period of time.
[0092] This embodiment provides a method for calculating the rectification effectiveness of a unit area in the current evaluation report:
[0093]
[0094] In the formula: T j NI represents the rectification effectiveness of the j-th unit area. j UDL represents the number of Class I hazard sources within the j-th unit area. j ′ ,a The risk level of the a-th Class I hazard source within the j-th unit area in the previous evaluation report is given by UDL in the current evaluation report. j,a Let be the risk quantification value of the risk level of the a-th Class I hazard source within the j-th unit area, and sigmoid() represents the normalization function.
[0095] By comparing the first-class hazards in the two evaluation reports, and statistically analyzing the newly added first-class hazards in the current evaluation report, the risk value of the newly added first-class hazards is calculated. One calculation method is given below:
[0096]
[0097] In the formula: C j NI represents the newly added risk value in the j-th unit region. ′ j NUDL represents the number of newly added Class I hazard sources within the j-th unit area. j,p This represents the risk level of the p-th newly added Class I hazard source within the j-th unit area, and sigmoid() represents the normalization function.
[0098] Module 106: Dynamic Risk Management Level Module.
[0099] The Dynamic Risk Management Level Module is used to obtain the dynamic risk indicator value of each unit area based on the rectification results and newly added risk values of each unit area; to obtain the dynamic risk management level of each unit area based on the dynamic risk indicator value of each unit area, the number of unit areas, and the risk similarity between any two unit areas; and to implement risk control based on the dynamic risk management level of each unit area.
[0100] Calculate the dynamic risk indicator values and combine them with the similarity between units to calculate the dynamic risk management level of each unit, and adjust the rectification requirements based on the dynamic risk management level.
[0101] This embodiment provides a method for calculating dynamic risk indicator values:
[0102]
[0103] In the formula: AD j T represents the dynamic risk index value of the j-th unit area. j C represents the rectification effectiveness of the j-th unit area. j Let represent the newly added risk value of the j-th unit region, and c represent the preset fifth constant.
[0104] It should be noted that adding 'c' to the denominator is to ensure that the denominator is not zero and that the formula holds true. This will be used as an example for explanation.
[0105] Calculate the dynamic risk management level of each unit based on the similarity between units:
[0106]
[0107] Where: ADL j AD represents the dynamic risk management level of the j-th unit area.j AD represents the dynamic risk index value of the j-th unit area. j′ Indicates the j-th ′ The risk dynamic indicator value for each unit area, SUD j,j′ Indicates the j-th unit region and the j-th unit region. ′ Risk similarity of each unit region, N j This represents the number of unit regions other than the j-th unit region.
[0108] In the above formula, ADL j The larger the value, the better the dynamic risk management level of the j-th unit area.
[0109] The dynamic risk management levels of all units and regions are input into the regulatory system, which then ranks and displays these levels and implements risk control measures. This involves providing varying degrees of oversight and supervision.
[0110] This embodiment presents a flowchart of a risk management process based on GIS information, such as... Figure 2 As shown.
[0111] The present invention also proposes a risk management device based on GIS information, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program stored in the memory to implement the steps of the aforementioned module of a risk management system based on GIS information.
[0112] This invention is now complete.
[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A risk management system based on GIS information, characterized in that, The system includes the following modules: Data acquisition module: used to obtain the number of Class I hazard sources in each unit area, the risk level of each Class I hazard source, and the risk quantification value of the risk level in the current evaluation report; Risk source similarity module: used to obtain the risk point name word vector and risk category word vector of each Class I hazard source in each unit area. Based on the risk point name word vector, risk category word vector and risk level quantification value of each Class I hazard source in each unit area, the risk source similarity between any two Class I hazard sources in any two unit areas is obtained. Traffic management cost similarity module: used to obtain the location information of each unit area, and based on the location information of each unit area, obtain the traffic management cost similarity between any two Class I hazard sources in any two unit areas; Risk Similarity Module: Used to obtain the risk similarity between any two unit areas based on the similarity of hazard sources and traffic management costs between any two Class I hazard sources within any two unit areas; The newly added risk value module is used to obtain the rectification effect and the newly added risk value for each unit area based on all Class I hazard sources, their risk levels, and the number of Class I hazard sources in each unit area in the current evaluation report. Dynamic Risk Management Level Module: Used to obtain dynamic risk indicator values for each unit / region based on the rectification results and newly added risk values. The dynamic risk management level of each unit area is obtained based on the dynamic risk indicator value of each unit area, the number of unit areas, and the risk similarity between any two unit areas; Risk control is implemented based on the dynamic risk management level of each unit / region.
2. The risk management system based on GIS information according to claim 1, characterized in that, The step of obtaining the hazard similarity between any two Class I hazard sources in any two unit areas based on the risk point name word vector, risk category word vector, and risk level quantification value of each Class I hazard source within each unit area includes: In the formula: This indicates that the a-th Class I hazard source within the j-th unit area is related to the j-th... ′ Within the unit region, the a-th ′ Hazard similarity among Category I hazard sources, UWD j,a UWD represents the word vector of the risk point name of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The risk point name word vector of a Class I hazard source, UWDC j,a UWDC represents the word vector representing the risk category of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The word vectors of the risk categories of the first-class hazard sources, UDL j,a UDL represents the risk quantification value of the risk level of the a-th Class I hazard source within the j-th unit area. j′,a′ Indicates the j-th ′ Within the unit region, the a-th ′ The risk quantification value of the risk level of a Class I hazard source, c represents the preset fifth constant, || represents removing the absolute value, sigmoid() represents the normalization function, and cos() is the cosine function.
3. The risk management system based on GIS information according to claim 1, characterized in that, The step of obtaining the similarity of traffic management costs between any two Class I hazard sources within any two unit areas based on the location information of each unit area includes: The location information of each unit area is mapped into GIS information. The road information of the nearest road to the risk point of each Class I hazard source in each unit area is identified in the GIS information. The road width, road tortuosity, and road undulation of the road where the risk point of each Class I hazard source is located in each unit area are obtained. The normalized value of the ratio of the product of the road undulation and the road tortuosity of the nearest road to each Class I hazard source within each unit area to the road width is used to obtain the traffic management cost of each Class I hazard source within each unit area. Based on the traffic management cost of each Class I hazard source within each unit area, obtain the similarity of traffic management costs between any two Class I hazard sources within any two unit areas.
4. The risk management system based on GIS information according to claim 3, characterized in that, The step of obtaining the similarity of traffic management costs between any two Class I hazard sources in any two unit areas based on the traffic management cost of each Class I hazard source in each unit area includes: Calculate the relationship between the a-th Class I hazard source and the j-th hazard source within the j-th unit area. ′ Within the unit region, the a-th ′ The absolute value of the difference in traffic management costs for each Class I hazard source; The difference between the preset sixth constant and the absolute value of the difference is denoted as the difference between the a-th Class I hazard source and the j-th Class II hazard source within the j-th unit area. ′ Within the unit region, the a-th ′ The similarity of traffic management costs among the first-class hazard sources.
5. The risk management system based on GIS information according to claim 1, characterized in that, The process of obtaining the risk similarity between any two unit areas based on the similarity of hazard sources and traffic management costs between any two Class I hazard sources within any two unit areas includes: Within the j-th unit area, the a-th Class I hazard source and the j-th ′ Among the similarity of all Class I hazard sources within a given unit area, the j-th hazard source with the highest similarity will be selected. ′ The first type of hazard source within a unit area is denoted as the matched hazard source of the first type of hazard source in the j-th unit area; At the jth ′ Within the unit region, the a-th ′ Among the similarity between a Class I hazard source and all Class I hazard sources within the j-th unit area, the Class I hazard source within the j-th unit area corresponding to the highest hazard source similarity is denoted as the j-th hazard source. ′ Within the unit region, the a-th ′ Matching hazards for each Class I hazard; Based on the j-th unit region and the j-th ′ By analyzing the similarity of each Class I hazard source within a given unit area with its matching hazard source and the similarity of traffic management costs, the risk similarity between any two unit areas can be obtained.
6. The risk management system based on GIS information according to claim 5, characterized in that, The condition based on the j-th unit region and the j-th ′ The risk similarity between each Class I hazard source and its matching hazard source within a given unit area is determined by the similarity of hazard sources and traffic management costs, and the risk similarity between any two unit areas is obtained by: Where: SUD j,j′ Indicates the j-th unit region and the j-th unit region. ′ Risk similarity of individual unit regions, NI j SR represents the number of Class I hazard sources within the j-th unit area. j ′ ,a,p SD represents the similarity of traffic management costs between the a-th Class I hazard source and its matching hazard source within the j-th unit area. j ′ ,a,p NI represents the hazard similarity between the a-th Class I hazard source and its matching hazard source within the j-th unit area. j′ Indicates the j-th ′ The number of Class I hazard sources within a unit area, SR j " ,a′,p′ Indicates the j-th ′ Within the unit region, the a-th ′ The similarity of traffic management costs between a Class I hazard source and its matching hazard sources, SD j " ,a′,p′ Indicates the j-th ′ Within the unit region, the a-th ′ The similarity of a Class I hazard source to its matching hazard source, where M represents a preset constant.
7. The risk management system based on GIS information according to claim 1, characterized in that, The process of obtaining the rectification effectiveness and newly added risk values for each unit area based on all Class I hazard sources, their risk levels, and the number of Class I hazard sources in the current evaluation report includes: Obtain the risk quantification value of the risk level of each Class I hazard source within each unit area from the previous evaluation report in the current evaluation report; The normalized value of the mean of the differences between the risk levels of all Class I hazard sources with the same sequence values in the j-th unit area of the current evaluation report and the previous evaluation report is recorded as the rectification effect of the j-th unit area. Compare the Class I hazards in the current evaluation report with those in the previous evaluation report, and compile statistics on the newly added Class I hazards in the current evaluation report; The normalized value of the mean risk level of all newly added Class I hazard sources in the j-th unit area is recorded as the newly added risk value of the j-th unit area.
8. The risk management system based on GIS information according to claim 1, characterized in that, The process of obtaining the dynamic risk indicator value for each unit area based on the rectification results and newly added risk values includes: Calculate the sum of the new risk value and the preset fifth constant for each unit area, and record the ratio of the rectification effect of each unit area to the sum as the risk dynamic indicator value of each unit area.
9. The risk management system based on GIS information according to claim 1, characterized in that, The process of obtaining the dynamic risk management level of each unit area based on its dynamic risk indicator value, the number of unit areas, and the risk similarity between any two unit areas includes: Where: ADL j AD represents the dynamic risk management level of the j-th unit area. j AD represents the dynamic risk index value of the j-th unit area. j′ Indicates the j-th ′ The risk dynamic indicator value for each unit area, SUD j,j′ Indicates the j-th unit region and the j-th unit region. ′ Risk similarity of each unit region, N j This represents the number of unit regions other than the j-th unit region.
10. A risk management device based on GIS information, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by the processor, it implements a module of a risk management system based on GIS information as described in any one of claims 1-9.