Regional risk determination method, apparatus, electronic device, and storage medium

Abstract

The present disclosure relates to a regional risk determination method and device, electronic equipment and storage medium. A set of basic indexes of at least one tailings pond in a target region is obtained, including a plurality of basic indexes with first category labels, and each first category label has a corresponding second category label. The risk index of the tailings pond is calculated according to each basic index and the corresponding first and second category labels. The corresponding risk weight of each tailings pond in the target region is determined according to the volume of each tailings pond, and the regional risk of the target region is determined according to the risk weight and the risk index of each tailings pond. The present disclosure calculates the regional risk by periodically obtaining the basic indexes of the tailings pond in the target region, reduces the possibility of safety hazards caused by tailings pond leakage, and improves the accuracy of the risk calculation result by double-labeling the basic indexes to calculate the risk of the tailings pond.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of computer, and particularly relates to a regional risk determination method and device, electronic equipment and storage medium. BACKGROUND

[0002] Tailings dam accidents occur from time to time, which greatly threatens the safety of people's life and property, and also brings serious harm to environmental safety. Therefore, it is necessary to prevent the occurrence of major production safety accidents of tailings dams from the source, to monitor and master the regional risk index of tailings dams in real time, and to improve the safety production risk perception ability of tailings dams. SUMMARY

[0003] Therefore, the present disclosure provides a regional risk determination method and device, electronic equipment and storage medium, which aims to monitor the risk of tailings dams in a specific region in real time.

[0004] According to a first aspect of the present disclosure, a regional risk determination method is provided, the method comprising:

[0005] obtaining a basic index set of at least one tailings dam in a target region, the basic index set comprising a plurality of basic indexes with first category labels, each first category label having a corresponding second category label;

[0006] calculating the plurality of basic indexes according to the first category label and the second category label corresponding to each basic index in the basic index set, to obtain a risk index of the corresponding tailings dam;

[0007] determining a risk weight corresponding to each tailings dam in the target region according to the volume of the tailings dam;

[0008] determining a regional risk of the target region according to the risk weight and the risk index of each tailings dam.

[0009] In a possible implementation, the calculation of the plurality of basic indexes according to the first category label and the second category label corresponding to each basic index in the basic index set to obtain a risk index of the corresponding tailings dam comprises:

[0010] calculating a weighted sum of the basic indexes corresponding to each first category label in the basic index set to obtain a first intermediate index corresponding to the first category label;

[0011] calculating a weighted sum of the first intermediate indexes corresponding to each first category label of the second category label to obtain a second intermediate index corresponding to the second category label;

[0012] calculating a weighted sum of each second intermediate index to obtain a risk index of the corresponding tailings dam of the basic index set.

[0013] In a possible implementation, the determining of the risk weight of each of the tailings ponds in the target region according to the volume of the tailings pond comprises:

[0014] calculating the volume of each of the tailings ponds in the target region and obtaining a region volume;

[0015] determining the risk weight of each of the tailings ponds according to a ratio of the volume of the tailings pond to the region volume.

[0016] In a possible implementation, the determining of the region risk of the target region according to the risk weight of each of the tailings ponds and the risk index comprises:

[0017] calculating a product of the risk index square of each of the tailings ponds in the target region and the risk weight, to obtain a feature parameter of each of the tailings ponds;

[0018] calculating a square root of a sum of the feature parameters of each of the tailings ponds, to obtain a region risk index of the target region;

[0019] determining the region risk of the target region according to the region risk index.

[0020] In a possible implementation, the obtaining of the basic index set of at least one tailings pond in the target region comprises:

[0021] periodically obtaining a plurality of original indexes of at least one tailings pond in the target region;

[0022] performing data filtering processing on the plurality of original indexes of each of the tailings ponds to obtain a corresponding basic index;

[0023] determining a corresponding basic index set according to the plurality of basic indexes of each of the tailings ponds.

[0024] In a possible implementation, the basic index set comprises at least one of a number of professional and technical personnel evaluation index, a number of professional management personnel evaluation index, a number of special operation personnel evaluation index, a static data quality evaluation index, a real-time data quality evaluation index, a tailings particle size evaluation index, a stacking bulk density evaluation index, a dam building method evaluation index, a safety super-high evaluation index, a dry beach length evaluation index, a current dam height evaluation index, an anti-seismic capacity evaluation index, a saturation line height evaluation index, a flood drainage method evaluation index, a flood drainage standard evaluation index, a foundation structure evaluation index, a terrain slope evaluation index, a rainfall evaluation index, a surface displacement evaluation index, an internal displacement evaluation index, a safety monitoring and early warning evaluation index, an emergency rescue plan and drilling evaluation index, a current grade evaluation index, a number of people in a 1-kilometer downstream evaluation index, and a number of buildings in a 1-kilometer downstream evaluation index.

[0025] In a possible implementation, the first category label includes personnel training, personnel quality, tailings properties, stacking system, flood drainage system, geological conditions, meteorological conditions, displacement monitoring, safety inspection and archive system, and accident prevention and emergency treatment.

[0026] The personnel training corresponds to basic indexes including professional technical personnel number evaluation index, professional management personnel number evaluation index, and special operation personnel number evaluation index. The personnel quality corresponds to basic indexes including static data quality evaluation index and real-time data quality evaluation index. The tailings properties correspond to basic indexes including tailings particle size evaluation index and stacking bulk density evaluation index. The stacking system corresponds to basic indexes including dam building mode evaluation index, safety superhigh evaluation index, dry beach length evaluation index, present dam height evaluation index, anti-seismic capacity evaluation index, and phreatic line height evaluation index. The flood drainage system corresponds to basic indexes including flood drainage mode evaluation index and flood drainage standard evaluation index. The geological conditions correspond to basic indexes including foundation structure evaluation index and terrain slope evaluation index. The meteorological conditions correspond to basic indexes including rainfall evaluation index. The displacement monitoring corresponds to basic indexes including surface displacement evaluation index and internal displacement evaluation index. The safety inspection and archive system corresponds to basic indexes including safety monitoring and early warning evaluation index. The accident prevention and emergency treatment corresponds to basic indexes including emergency rescue plan and drilling evaluation index, present classification evaluation index, total number of people within 1 km downstream evaluation index, and number of buildings within 1 km downstream evaluation index.

[0027] In a possible implementation, the second category label includes human factor, technical factor, environmental factor, and management factor.

[0028] The human factor corresponds to first category labels including personnel training and personnel quality. The technical factor corresponds to first category labels including tailings properties, stacking system, and flood drainage system. The environmental factor corresponds to first category labels including geological conditions, meteorological conditions, and displacement monitoring. The management factor corresponds to first category labels including safety inspection and archive system, and accident prevention and emergency treatment.

[0029] In a possible implementation, the method further includes:

[0030] In response to the area risk being higher than a preset risk threshold, performing corresponding risk warning based on a map.

[0031] In a possible implementation, the performing corresponding risk warning based on a map includes:

[0032] Highlighting or flickering a position corresponding to the target area in the map.

[0033] In a possible implementation, the method further includes:

[0034] In response to receiving the access request sent by the user based on the risk warning, the region risk information corresponding to the target region is generated and displayed, and the region risk information includes at least one of a region risk, a risk type, a risk level, a risk index, and a responsibility subject.

[0035] According to a second aspect of the present disclosure, a region risk determination apparatus is provided, and the apparatus includes:

[0036] An index acquisition module is configured to acquire a basic index set of at least one tailings pond in a target region, and the basic index set includes a plurality of basic indexes with first category labels, and each first category label has a corresponding second category label.

[0037] An index calculation module is configured to calculate the plurality of basic indexes according to the first category label and the second category label corresponding to each basic index in the basic index set, to obtain a risk index of the corresponding tailings pond.

[0038] A weight determination module is configured to determine a risk weight of each tailings pond in the target region according to the volume of the tailings pond.

[0039] A region risk determination module is configured to determine a region risk of the target region according to the risk weight and the risk index of each tailings pond.

[0040] In a possible implementation, the index calculation module includes:

[0041] A first index calculation submodule is configured to calculate a weighted sum of the basic index corresponding to each first category label in the basic index set, to obtain a first intermediate index corresponding to the first category label.

[0042] A second index calculation submodule is configured to calculate a weighted sum of the first intermediate index corresponding to each second category label, to obtain a second intermediate index corresponding to the second category label.

[0043] A third index calculation submodule is configured to calculate a weighted sum of each second intermediate index, to obtain a risk index of the tailings pond corresponding to the basic index set.

[0044] In a possible implementation, the weight determination module includes:

[0045] A volume calculation submodule is configured to calculate the volume of each tailings pond in the target region and obtain a region volume.

[0046] The weight calculation submodule is configured to determine the risk weight of each tailing pond according to the ratio of the volume of each tailing pond to the volume of the region.

[0047] In a possible implementation, the regional risk determination module comprises:

[0048] The feature parameter determination submodule is configured to calculate the product of the risk index square of each tailing pond in the target region and the risk weight to obtain a feature parameter of each tailing pond.

[0049] The index calculation submodule is configured to calculate the square root of the sum of the feature parameters of each tailing pond to obtain a regional risk index of the target region.

[0050] The regional risk determination submodule is configured to determine the regional risk of the target region according to the regional risk index.

[0051] In a possible implementation, the index acquisition module comprises:

[0052] The period acquisition submodule is configured to periodically acquire a plurality of original indexes of at least one tailing pond in a target region.

[0053] The data filtering submodule is configured to perform data filtering processing on the plurality of original indexes of each tailing pond to obtain a corresponding basic index.

[0054] The set determination submodule is configured to determine a corresponding basic index set according to the plurality of basic indexes of each tailing pond.

[0055] In a possible implementation, the basic index set comprises at least one of the following: a number of professional and technical personnel evaluation index, a number of professional management personnel evaluation index, a number of special operation personnel evaluation index, a static data quality evaluation index, a real-time data quality evaluation index, a tailing particle size evaluation index, a stacking bulk density evaluation index, a dam building method evaluation index, a safety super-high evaluation index, a dry beach length evaluation index, a current dam height evaluation index, an anti-seismic capacity evaluation index, a saturation line height evaluation index, a flood drainage method evaluation index, a flood drainage standard evaluation index, a foundation structure evaluation index, a terrain slope evaluation index, a rainfall evaluation index, a surface displacement evaluation index, an internal displacement evaluation index, a safety monitoring and early warning evaluation index, an emergency rescue plan and drilling evaluation index, a current grade evaluation index, a number of people within 1 km downstream evaluation index, and a number of buildings within 1 km downstream evaluation index.

[0056] In a possible implementation, the first category label comprises personnel training, personnel quality, tailing properties, stacking system, flood drainage system, geological conditions, meteorological conditions, displacement monitoring, safety inspection and archive system, and accident prevention and emergency handling.

[0057] The basic indexes corresponding to the personnel training include a professional and technical personnel number evaluation index, a professional management personnel number evaluation index, and a special operation personnel number evaluation index, the basic indexes corresponding to the personnel quality include a static data quality evaluation index and a real-time data quality evaluation index, the basic indexes corresponding to the tailings properties include a tailings particle size evaluation index and a stacking bulk density evaluation index, the basic indexes corresponding to the stacking system include a dam building mode evaluation index, a safety superhigh evaluation index, a dry beach length evaluation index, a current dam height evaluation index, an anti-seismic capability evaluation index, and a phreatic line height evaluation index, the basic indexes corresponding to the flood drainage system include a flood drainage mode evaluation index and a flood drainage standard evaluation index, the basic indexes corresponding to the geological conditions include a foundation structure evaluation index and a terrain slope evaluation index, the basic indexes corresponding to the meteorological conditions include a rainfall evaluation index, the basic indexes corresponding to the displacement monitoring include a surface displacement evaluation index and an internal displacement evaluation index, the basic indexes corresponding to the safety inspection and archive system include a safety monitoring and early warning evaluation index, and the basic indexes corresponding to the accident prevention and emergency treatment include an emergency rescue plan and drilling evaluation index, a current classification evaluation index, a total number of people within 1 km downstream evaluation index, and a number of buildings within 1 km downstream evaluation index.

[0058] In a possible implementation, the second category label includes a human factor, a technical factor, an environmental factor, and a management factor.

[0059] The first category label corresponding to the human factor includes personnel training and personnel quality, the first category label corresponding to the technical factor includes tailings properties, a stacking system, and a flood drainage system, the first category label corresponding to the environmental factor includes geological conditions, meteorological conditions, and displacement monitoring, and the first category label corresponding to the management factor includes a safety inspection and archive system and accident prevention and emergency treatment.

[0060] In a possible implementation, the apparatus further includes:

[0061] A risk warning module configured to, in response to the regional risk being higher than a preset risk threshold, perform corresponding risk warning based on the map.

[0062] In a possible implementation, the risk warning module includes:

[0063] A risk prompt sub-module configured to highlight or flash a position corresponding to the target region in the map.

[0064] In a possible implementation, the apparatus further includes:

[0065] The information display module is configured to generate and display regional risk information corresponding to the target region in response to receiving an access request sent by a user based on the risk warning, wherein the regional risk information comprises at least one of a regional risk, a risk type, a risk level, a risk index, and a responsible subject.

[0066] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0067] According to a fourth aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, which stores computer program instructions, wherein the computer program instructions are executed by a processor to implement the above method.

[0068] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device executes the above method.

[0069] In the embodiments of the present disclosure, a set of basic indexes of at least one tailing pond in a target region is obtained, wherein the set of basic indexes comprises a plurality of basic indexes with first category labels, and each first category label has a corresponding second category label. The risk index of the tailing pond is calculated according to each basic index and the corresponding first category label and second category label. The risk weight of each tailing pond in the target region is determined according to the volume of the tailing pond, and the regional risk of the target region is determined according to the risk weight and the risk index of each tailing pond. The present disclosure calculates the regional risk by periodically obtaining the basic indexes of the tailing ponds in the target region, reduces the possibility of safety hazards caused by tailing pond leakage, and improves the accuracy of the risk calculation result by double-labeling the basic indexes to calculate the risk of the tailing pond.

[0070] Other features and aspects of the present disclosure will become apparent from the following detailed description of example embodiments with reference to the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0071] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate example embodiments, features, and aspects of the present disclosure and serve to explain the principles of the present disclosure.

[0072] Figure 1 A flowchart of a method for determining a regional risk according to an embodiment of the present disclosure is shown;

[0073] Figure 2A schematic diagram showing a method for determining a risk index of a tailings pond according to an embodiment of the present disclosure is shown.

[0074] Figure 3 A schematic diagram showing a regional risk determination apparatus according to an embodiment of the present disclosure is shown.

[0075] Figure 4 A schematic diagram showing an electronic device according to an embodiment of the present disclosure is shown.

[0076] Figure 5 A schematic diagram showing another electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0077] Various exemplary embodiments, features and aspects of the present disclosure will be explained in detail below with reference to the accompanying drawings. The same reference numbers in different drawings denote the same or similar elements / functionally similar elements. Although various aspects of the embodiments are illustrated in the drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0078] The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any implementation described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other implementations.

[0079] In addition, for the sake of brevity, a number of specific details are not described in detail herein. Those skilled in the art should understand that the various embodiments described and pictured herein can be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been described in detail in order to avoid obscuring the subject matter of the present disclosure.

[0080] In one possible implementation, the regional risk determination method of the embodiments of the present disclosure can be executed by an electronic device such as a processor, a terminal device, or a server. The terminal device can be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, and the like. The server can be a single server or a server cluster composed of multiple servers. The electronic device can implement the regional risk determination method of the embodiments of the present disclosure by invoking computer-readable instructions stored in a memory through a processor.

[0081] Figure 1 A flowchart of a regional risk determination method according to an embodiment of the present disclosure is shown. As shown in Figure 1 The regional risk determination method of the embodiments of the present disclosure can include the following steps S10-S40.

[0082] In step S10, a basic index set of at least one tailings pond in the target region is obtained.

[0083] In a possible implementation, the basic index set of at least one tailings pond in the target region can be determined periodically by the electronic device. The target region is a region including at least one tailings pond, and the dam-break risk of the tailings pond needs to be monitored. The target region can be a province, a city, a county, or other pre-divided geographical region. The basic index set of each tailings pond in the target region can include a plurality of basic indexes for evaluating the risk of the tailings pond, for example, at least one of the following indexes: a number of professional and technical personnel evaluation index, a number of professional management personnel evaluation index, a number of special operation personnel evaluation index, a static data quality evaluation index, a real-time data quality evaluation index, a tailings particle size evaluation index, a stacking bulk density evaluation index, a dam building method evaluation index, a safety super-high evaluation index, a dry beach length evaluation index, a current dam height evaluation index, an anti-seismic capability evaluation index, a saturation line height evaluation index, a flood drainage method evaluation index, a flood drainage standard evaluation index, a foundation structure evaluation index, a terrain slope evaluation index, a rainfall evaluation index, a surface displacement evaluation index, an internal displacement evaluation index, a safety monitoring and early warning evaluation index, an emergency rescue plan and drilling evaluation index, a current classification evaluation index, a total number of people in the downstream 1 km evaluation index, and a number of buildings in the downstream 1 km evaluation index, which are respectively used to evaluate the risk of the tailings pond from the corresponding dimension.

[0084] Optionally, the plurality of basic indexes included in the basic index set each have a corresponding first category label, and different basic indexes can correspond to the same first category label. Exemplarily, the first category label of the embodiment of the present disclosure can include personnel training, personnel quality, tailings properties, stacking system, flood drainage system, geological conditions, weather conditions, displacement monitoring, safety inspection and archive system, and accident prevention and emergency handling. Among them, the basic indexes corresponding to personnel training include professional and technical personnel number evaluation index, professional management personnel number evaluation index and special operation personnel number evaluation index, the basic indexes corresponding to personnel quality include static data quality evaluation index and real-time data quality evaluation index, the basic indexes corresponding to tailings properties include tailings particle size evaluation index and stacking bulk density evaluation index, the basic indexes corresponding to stacking system include dam building method evaluation index, safety superhigh evaluation index, dry beach length evaluation index, current dam height evaluation index, anti-seismic capacity evaluation index and phreatic line height evaluation index, the basic indexes corresponding to flood drainage system include flood drainage method evaluation index and flood drainage standard evaluation index, the basic indexes corresponding to geological conditions include foundation structure evaluation index and terrain slope evaluation index, the basic indexes corresponding to weather conditions include rainfall evaluation index, the basic indexes corresponding to displacement monitoring include surface displacement evaluation index and internal displacement evaluation index, the basic indexes corresponding to safety inspection and archive system include safety monitoring and early warning evaluation index, and the basic indexes corresponding to accident prevention and emergency handling include emergency rescue plan and drilling evaluation index, current classification evaluation index, downstream 1 kilometer total number evaluation index and downstream 1 kilometer building number evaluation index.

[0085] Optionally, the first category label corresponding to each basic index in the basic index set can also have a corresponding second category label, and different first category labels can correspond to the same second category label. Exemplarily, the second category label of the embodiment of the present disclosure can include human factors, technical factors, environmental factors and management factors. Among them, the first category label corresponding to human factors includes personnel training and personnel quality, the first category label corresponding to technical factors includes tailings properties, stacking system and flood drainage system, the first category label corresponding to environmental factors includes geological conditions, weather conditions and displacement monitoring, and the first category label corresponding to management factors includes safety inspection and archive system and accident prevention and emergency handling.

[0086] Further, the basic indexes in the basic index set of each tailings pond can be periodically detected by the sensors installed in the tailings pond and transmitted to the database to store the basic index set. Alternatively, the electronic device can further store the basic index set in the database after filtering the data of the obtained multiple basic indexes. That is, the electronic device can periodically obtain multiple original indexes of at least one tailings pond in the target area, and then filter the data of the multiple original indexes of each tailings pond to obtain the corresponding basic indexes, and determine the corresponding basic index set according to the multiple basic indexes of each tailings pond. The data filtering process can include data bit padding, filtering of high values, and filtering of low values. For example, the sensors installed in the tailings pond can periodically transmit the periodically detected basic indexes to the original database, and store the basic index set in the business database after filtering the data of each basic index.

[0087] In step S20, the multiple basic indexes are calculated according to the first category label and the second category label corresponding to each basic index in the basic index set, to obtain the risk index of the corresponding tailings pond.

[0088] In a possible implementation, after the electronic device determines the basic index set corresponding to each tailings pond, the multiple basic indexes are calculated according to the first category label and the second category label corresponding to each basic index, to obtain the risk index of the corresponding tailings pond. The risk index of the tailings pond is used to represent the risk of dam failure of the tailings pond. Alternatively, the hierarchical calculation process can be to first calculate the weighted sum of the basic indexes corresponding to each first category label in the basic index set to obtain the first intermediate index corresponding to the first category label. Then, the weighted sum of the first intermediate indexes corresponding to each second category label of the first category label is calculated to obtain the second intermediate index corresponding to the second category label. Finally, the weighted sum of each second intermediate index is calculated to obtain the risk index of the tailings pond corresponding to the basic index set.

[0089] For example, the embodiments of the present disclosure can regard the basic indexes as the first layer indexes D, the first category labels as the second layer indexes C, the second category labels as the third layer indexes B, and the risk indexes as the fourth layer indexes A. The electronic device can calculate the weighted sum of the values of at least one first layer index D corresponding to each second layer index C to obtain the value of each second layer index C, that is, the first intermediate index. Then, the weighted sum of the values of at least one second layer index C corresponding to each third layer index B is calculated to obtain the value of each third layer index B, that is, the second intermediate index. Finally, the weighted sum of the values of multiple third layer indexes B is calculated to obtain the value of the fourth layer index A, that is, the risk index.

[0090] For example, the electronic device can determine the risk index of the tailings pond layer by layer through the corresponding relationship in Table 1, Table 2 and Table 3 as follows.

[0091] Table 1

[0092]

[0093]

[0094] Table 2

[0095]

[0096] Table 3

[0097]

[0098]

[0099] As shown in Tables 1, 2, and 3 above, the first layer of indicators includes 24 basic indicators. Starting from these basic indicators, the indicators are calculated layer by layer upwards based on their weights and values, ultimately yielding the tailings dam risk indicators for the top fourth layer. Each layer is calculated as a weighted sum of its parameters; the formula for calculating one indicator value at each layer is as follows: Where n is the number of corresponding lower-level indicators, P i Q represents the value of the lower-level indicator. i This represents the weight of the lower-level indicator values. Optionally, the risk indicator of the tailings dam can be obtained directly by weighting according to the indicator value calculation formula, i.e., P... i The value of Q is considered as a basic indicator. i The weights of basic indicator values ​​are calculated using a hierarchical cumulative weighting method. A judgment matrix is ​​created hierarchically, and the indicator weights are determined using hierarchical analysis. After calculating the relative weight of each indicator within its respective level and category, the cumulative weight of all evaluation indicators with respect to the overall objective is determined using a weighted product method. For example, basic indicator D... i The corresponding first category label, i.e., the second-level indicator, is C. j And the first category label C j The corresponding second category label, i.e., the third-level indicator, is B. k In the case of indicator D i The cumulative weight is: Therefore, it can be calculated directly. Obtain risk indicators for tailings ponds.

[0100] Figure 2 A schematic diagram illustrating one method for determining risk indicators for tailings ponds according to an embodiment of this disclosure is shown. Figure 2As shown, the risk indicator of the embodiment of the present disclosure can be determined in a hierarchical calculation manner. In calculating the risk indicator of each tailings pond, the electronic device can calculate the value corresponding to each first category label according to each basic indicator 20 and the corresponding first category label 21 in the basic indicator set corresponding to the tailings pond as a first intermediate indicator 22. Further, according to the corresponding relationship between the first category label 21 and the second category label 23, the value corresponding to the first intermediate indicator 22 of each second category label 23 corresponding to the first category label 21 is calculated as a second intermediate indicator 24. Finally, the weighted sum of the plurality of second intermediate indicators 24 is calculated to obtain the risk indicator 25 of the tailings pond, which is used to represent the dam-break risk of the tailings pond.

[0101] Step S30, determining the corresponding risk weight according to the volume of each tailings pond in the target area.

[0102] In a possible implementation, since the larger the tailings pond is, the greater the dam-break risk is, the electronic device can determine the volume of each tailings pond in the target area, and determine the corresponding risk weight according to the volume of the tailings pond. That is, the electronic device can first determine the volume of each tailings pond in the target area, then calculate the volume of each tailings pond in the target area to obtain the area volume, and determine the risk weight of the tailings pond according to the ratio of the volume of each tailings pond to the area volume. Wherein, the volume of each tailings pond is the inherent attribute of the tailings pond, which can be determined in advance. For example, in the case that the target area includes n tailings ponds, the risk weight corresponding to the i th tailings pond can be calculated by the formula . Wherein, V is the volume of the tailings pond.

[0103] Step S40, determining the area risk of the target area according to the risk weight and the risk indicator of each tailings pond.

[0104] In a possible implementation, after determining the risk weight and the risk indicator of each tailings pond in the target area, the electronic device can determine the area risk of the target area according to the risk weight and the risk indicator of each tailings pond. Alternatively, the area risk can be determined in any manner, for example, by calculating the weighted sum of the risk indicators of each tailings pond in the target area. Or, according to the risk weight and the risk indicator of each tailings pond in the target area, the corresponding feature parameter is calculated, and then the area risk of the target area is determined according to the feature parameters of the plurality of tailings ponds.

[0105] Alternatively, the electronic device can first calculate the product of the square of the risk indicator and the risk weight of each tailings pond in the target area to obtain the feature parameter of each tailings pond. Then, the square root of the sum of the feature parameters of each tailings pond is calculated to obtain the area risk index of the target area. Then, the area risk of the target area is determined according to the area risk index. That is, the area risk of the target area can be calculated by the formula D is determined, wherein D is a regional risk index of the target region, D i is a risk index of the i th tailing pond in the target region, w i is a risk weight of the i th tailing pond in the target region. After determining the regional risk index, the regional risk index can be directly used as a regional risk for characterizing the risk intensity in the region. Alternatively, according to the size of the regional risk index and the risk index ranges corresponding to the preset multiple regional risks “high”, “medium” and “low”, respectively, the corresponding regional risk is determined.

[0106] In a possible implementation, the electronic device can further prompt the user of the risk through a map based on the regional risk of the target region. The map can be any map, for example, a GIS map. In the case where the regional risk of the target region is higher than a preset risk threshold, the electronic device can perform corresponding risk warning based on the map. The manner of the risk warning can be highlighting or flickering the position corresponding to the target region in the map.

[0107] Further, the electronic device can also interact with the user based on the GIS map, that is, in response to receiving an access request sent by the user based on the risk warning, generate and display the regional risk information corresponding to the target region, wherein the regional risk information includes at least one of the regional risk, the risk type, the risk level, the risk index and the responsible subject. The access situation can be generated when the user triggers the position of the target region in the GIS map in a sliding, clicking or other manner.

[0108] Based on the above technical features, the embodiments of the present disclosure can reduce the possibility of safety hazards caused by tailing pond leakage by periodically acquiring the basic indicators of the tailing ponds in the target region to calculate the regional risk, and improve the accuracy of the risk calculation result by double-labeling the basic indicators to calculate the risk of the tailing pond. At the same time, the embodiments of the present disclosure can also prompt the user of the risk through a map after determining the regional risk, and interact with the user to improve the user experience.

[0109] Figure 3 A schematic diagram of a regional risk determination apparatus according to an embodiment of the present disclosure is shown. As shown in Figure 3 The regional risk determination apparatus of the present disclosure can include:

[0110] The index acquisition module 30 is configured to acquire a basic indicator set of at least one tailing pond in a target region, wherein the basic indicator set includes a plurality of basic indicators with first category labels, and each first category label has a corresponding second category label.

[0111] The index calculation module 31 is configured to calculate the plurality of basic indexes of the tailing pond according to the first category label and the second category label corresponding to each basic index in the basic index set, and obtain the risk index of the tailing pond.

[0112] The weight determination module 32 is configured to determine the risk weight of each tailing pond in the target area according to the volume of the tailing pond.

[0113] The regional risk determination module 33 is configured to determine the regional risk of the target area according to the risk weight and the risk index of each tailing pond.

[0114] In a possible implementation, the index calculation module 31 comprises:

[0115] The first index calculation submodule is configured to calculate the weighted sum of the basic index corresponding to each first category label in the basic index set, and obtain the first intermediate index corresponding to the first category label.

[0116] The second index calculation submodule is configured to calculate the weighted sum of the first intermediate index corresponding to each second category label, and obtain the second intermediate index corresponding to the second category label.

[0117] The third index calculation submodule is configured to calculate the weighted sum of each second intermediate index, and obtain the risk index of the tailing pond corresponding to the basic index set.

[0118] In a possible implementation, the weight determination module 32 comprises:

[0119] The volume calculation submodule is configured to calculate the volume of each tailing pond in the target area and obtain the regional volume.

[0120] The weight calculation submodule is configured to determine the risk weight of each tailing pond according to the ratio of the volume of the tailing pond to the regional volume.

[0121] In a possible implementation, the regional risk determination module 33 comprises:

[0122] The characteristic parameter determination submodule is configured to calculate the product of the risk index square of each tailing pond in the target area and the risk weight, and obtain the characteristic parameter of each tailing pond.

[0123] The index calculation submodule is configured to calculate the square root of the sum of the characteristic parameters of each tailing pond, and obtain the regional risk index of the target area.

[0124] The regional risk determination submodule is configured to determine the regional risk of the target area according to the regional risk index.

[0125] In a possible implementation, the index acquisition module 30 comprises:

[0126] a periodic acquisition sub-module, configured to periodically acquire a plurality of original indexes of at least one tailing pond in the target region;

[0127] a data filtering sub-module, configured to perform data filtering processing on the plurality of original indexes of each tailing pond to obtain a corresponding basic index;

[0128] a set determination sub-module, configured to determine a corresponding basic index set according to the plurality of basic indexes of each tailing pond.

[0129] In a possible implementation, the basic index set comprises at least one of a number of professional technicians evaluation index, a number of professional managers evaluation index, a number of special operation personnel evaluation index, a static data quality evaluation index, a real-time data quality evaluation index, a tailing particle size evaluation index, a stacking bulk density evaluation index, a dam building mode evaluation index, a safety superhigh evaluation index, a dry beach length evaluation index, a current dam height evaluation index, an anti-seismic capability evaluation index, an infiltration line height evaluation index, a flood drainage mode evaluation index, a flood drainage standard evaluation index, a foundation structure evaluation index, a terrain slope evaluation index, a rainfall evaluation index, a surface displacement evaluation index, an internal displacement evaluation index, a safety monitoring and early warning evaluation index, an emergency rescue plan and drilling evaluation index, a current grade evaluation index, a number of people in a 1-kilometer downstream evaluation index, and a number of buildings in a 1-kilometer downstream evaluation index.

[0130] In a possible implementation, the first category label comprises personnel training, personnel quality, tailing property, stacking system, flood drainage system, geological condition, meteorological condition, displacement monitoring, safety inspection and archive system, and accident prevention and emergency handling.

[0131] The basic indexes corresponding to the personnel training include a professional and technical personnel number evaluation index, a professional management personnel number evaluation index and a special operation personnel number evaluation index, the basic indexes corresponding to the personnel quality include static data quality evaluation indexes and real-time data quality evaluation indexes, the basic indexes corresponding to the tailings properties include tailings granularity evaluation indexes and stacking bulk density evaluation indexes, the basic indexes corresponding to the stacking system include dam building mode evaluation indexes, safety superhigh evaluation indexes, dry beach length evaluation indexes, present dam height evaluation indexes, anti-seismic capacity evaluation indexes and phreatic line height evaluation indexes, the basic indexes corresponding to the flood drainage system include flood drainage mode evaluation indexes and flood drainage standard evaluation indexes, the basic indexes corresponding to the geological conditions include foundation structure evaluation indexes and terrain slope evaluation indexes, the basic indexes corresponding to the meteorological conditions include rainfall evaluation indexes, the basic indexes corresponding to the displacement monitoring include surface displacement evaluation indexes and internal displacement evaluation indexes, the basic indexes corresponding to the safety inspection and archive system include safety monitoring and early warning evaluation indexes, and the basic indexes corresponding to the accident prevention and emergency treatment include emergency rescue plan and drilling evaluation indexes, present classification evaluation indexes, downstream 1-kilometer total number evaluation indexes and downstream 1-kilometer building number evaluation indexes.

[0132] In a possible implementation, the second category label includes human factors, technical factors, environmental factors and management factors.

[0133] The first category label corresponding to the human factors includes personnel training and personnel quality, the first category label corresponding to the technical factors includes tailings properties, stacking system and flood drainage system, the first category label corresponding to the environmental factors includes geological conditions, meteorological conditions and displacement monitoring, and the first category label corresponding to the management factors includes safety inspection and archive system and accident prevention and emergency treatment.

[0134] In a possible implementation, the device further includes:

[0135] The risk warning module is configured to, in response to the regional risk being higher than a preset risk threshold, perform corresponding risk warning based on the map.

[0136] In a possible implementation, the risk warning module includes:

[0137] The risk prompt sub-module is configured to highlight or flash at a position corresponding to the target region in the map.

[0138] In a possible implementation, the device further includes:

[0139] The information display module is configured to generate and display the region risk information corresponding to the target region in response to receiving the access request sent by the user based on the risk warning, wherein the region risk information comprises at least one of region risk, risk type, risk level, risk index, and responsibility subject.

[0140] In some embodiments, the apparatus provided by the embodiments of the present disclosure has functions or includes modules that can be used to perform the methods described in the above method embodiments, and the specific implementation can refer to the description of the above method embodiments. For brevity, details are not repeated here.

[0141] The embodiments of the present disclosure also provide a computer-readable storage medium having computer program instructions stored therein, and the computer program instructions are executed by a processor to implement the above method. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0142] The embodiments of the present disclosure also provide an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0143] The embodiments of the present disclosure also provide a computer program product, including computer readable code or a non-volatile computer readable storage medium carrying computer readable code, when the computer readable code is run in the processor of the electronic device, the processor in the electronic device executes the above method.

[0144] Figure 4 A schematic diagram of an electronic device 800 according to an embodiment of the present disclosure is shown. For example, the electronic device 800 can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0145] Referring to Figure 4 The electronic device 800 can include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0146] The processing component 802 generally controls the overall operations of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 can include one or more processors 820 to execute instructions to complete the steps of the methods described above, in whole or in part. Moreover, the processing component 802 can include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0147] The memory 804 is configured to store various types of data to support the operations of the electronic device 800. Examples of these data include instructions to operate any applications or methods on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and the like. The memory 804 can be realized by any type of volatile or non-volatile memory devices or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disc, or optical disc.

[0148] The power component 806 provides power to the various components of the electronic device 800. The power component 806 can include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0149] The multimedia component 808 includes a screen to provide an output interface between the electronic device 800 and a user. In some embodiments, the screen can include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes the touch panel, the screen can be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense a touch, a slide, and a gesture on the touch panel. The touch sensor can not only sense a boundary of a touching or a sliding action, but also detect duration and pressure related to the touching or sliding action. In some embodiments, the multimedia component 808 includes a front camera and / or a back camera. The front camera and / or the back camera can receive external multimedia data when the electronic device 800 is in an operating mode, such as a shooting mode or a video mode. Each of the front camera and the back camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0150] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC) that is configured to receive an external audio signal when the electronic device 800 is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0151] The I / O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which can include a keypad, a click wheel, buttons, and so on. The buttons can include, but are not limited to, a home button, a volume button, a start button, and a lock button.

[0152] The sensor component 814 includes one or more sensors for providing status assessments of various aspects of the electronic device 800. For example, the sensor component 814 can detect an open / closed position of the electronic device 800, relative positioning of components, such as a display and a keypad of the electronic device 800, a change of position of the electronic device 800 or a component of the electronic device 800, presence or absence of user contact with the electronic device 800, orientation or acceleration / deceleration of the electronic device 800, and temperature changes of the electronic device 800. The sensor component 814 can include a proximity sensor configured to detect presence of a nearby object without any physical touch. The sensor component 814 can also include a light sensor, such as a CMOS or CCD image sensor, for use in an imaging application. In some embodiments, the sensor component 814 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0153] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a corresponding communication standard, such as WiFi, 2G, or 3G, or a combination thereof. In an example embodiment, the communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an example embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technology.

[0154] In exemplary embodiments, the electronic device 800 can be implemented with one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic elements, for performing the above-described methods.

[0155] In exemplary embodiments, a non-transitory computer readable storage medium, such as the memory 804 including computer program instructions, is also provided, which can be executed by the processor 820 of the electronic device 800 to complete the above-described methods.

[0156] Figure 5 A schematic diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. For example, the electronic device 1900 can be provided as a server or a terminal device. Referring to Figure 5 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932, for storing instructions, such as application programs, executable by the processing component 1922. The application programs stored in the memory 1932 can include one or more than one module each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute the instructions to perform the above-described methods.

[0157] The electronic device 1900 can also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output (I / O) interface 1958. The electronic device 1900 can operate based on an operating system stored in the memory 1932, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.

[0158] In exemplary embodiments, a non-transitory computer readable storage medium, such as the memory 1932 including computer program instructions, is also provided, which can be executed by the processing component 1922 of the electronic device 1900 to complete the above-described methods.

[0159] The present disclosure can be a system, a method, and / or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

[0160] Computer readable storage media can be tangible storage media which can retain and store instructions for use by an instruction execution device. Computer readable storage media can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer readable storage media include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0161] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0162] Computer readable program instructions for carrying out operations of the present disclosure can be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate array (FPGA), or programmable logic array (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0163] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0164] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0165] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0166] The flow diagrams and the block diagrams in the drawings are presented to illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flow diagrams and the block diagrams can represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logic functions. In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and

[0167] Embodiments of the present disclosure have been described above, and the description is intended to be illustrative of the embodiments and not restrictive. Many modifications and variations of the described embodiments are possible and are within the scope of the disclosure. The selection of terms is intended to best describe the principles of the embodiments, practical application, or technical improvements in the art, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method of determining regional risk, characterized by, The method comprises: obtaining a basic index set of at least one tailings pond in a target area, the basic index set comprising a plurality of basic indexes with first category labels, each first category label having a corresponding second category label; calculating the plurality of basic indexes according to the first category label and the second category label corresponding to each basic index in the basic index set to obtain a risk index of the corresponding tailings pond; determining a risk weight corresponding to each tailings pond in the target area according to the volume of the tailings pond; determining a regional risk of the target area according to the risk weight and the risk index of each tailings pond; wherein the determination of the regional risk of the target area according to the risk weight and the risk index of each tailings pond comprises: calculating the product of the square of the risk index of each tailings pond in the target area and the risk weight to obtain a characteristic parameter of each tailings pond; calculating the square root of the sum of the characteristic parameters of each tailings pond to obtain a regional risk index of the target area; determining the regional risk of the target area according to the regional risk index; wherein the determination of the risk weight corresponding to each tailings pond in the target area according to the volume of the tailings pond comprises: calculating the sum of the volumes of each tailings pond in the target area to obtain a regional volume; determining the risk weight of the tailings pond according to the ratio of the volume of each tailings pond to the regional volume.

2. The method of claim 1, wherein, The calculation of the plurality of basic indexes according to the first category label and the second category label corresponding to each basic index in the basic index set to obtain a risk index of the corresponding tailings pond comprises: calculating the weighted sum of the basic indexes corresponding to each first category label in the basic index set to obtain a first intermediate index corresponding to the first category label; calculating the weighted sum of the first intermediate indexes corresponding to each first category label of each second category label to obtain a second intermediate index corresponding to the second category label; calculating the weighted sum of each second intermediate index to obtain a risk index of the corresponding tailings pond of the basic index set.

3. The method according to claim 1 or 2, characterized in that, The obtaining of the basic index set of at least one tailings pond in the target area comprises: periodically obtaining a plurality of original indexes of at least one tailings pond in the target area; performing data filtering processing on the plurality of original indexes of each tailings pond to obtain corresponding basic indexes; determining a corresponding basic index set according to the plurality of basic indexes of each tailings pond.

4. The method of claim 1, wherein, The basic index set includes at least one of the following: the number of professional and technical personnel evaluation index, the number of professional management personnel evaluation index, the number of special operation personnel evaluation index, static data quality evaluation index, real-time data quality evaluation index, tailings particle size evaluation index, pile bulk density evaluation index, dam building method evaluation index, safety super-high evaluation index, dry beach length evaluation index, current dam height evaluation index, seismic resistance evaluation index, phreatic line height evaluation index, flood drainage method evaluation index, flood drainage standard evaluation index, foundation structure evaluation index, terrain slope evaluation index, rainfall evaluation index, surface displacement evaluation index, internal displacement evaluation index, safety monitoring and early warning evaluation index, emergency rescue plan and drilling evaluation index, current grade evaluation index, downstream 1km total number of people evaluation index and downstream 1km building number evaluation index.

5. The method of claim 4, wherein, The first category label includes personnel training, personnel quality, tailings properties, stacking system, flood drainage system, geological conditions, meteorological conditions, displacement monitoring, safety inspection and archive system, and accident prevention and emergency handling. The personnel training corresponds to the number of professional and technical personnel evaluation index, the number of professional management personnel evaluation index and the number of special operation personnel evaluation index, the personnel quality corresponds to the static data quality evaluation index and the real-time data quality evaluation index, the tailings properties correspond to the tailings particle size evaluation index and the pile bulk density evaluation index, the stacking system corresponds to the dam building method evaluation index, the safety super-high evaluation index, the dry beach length evaluation index, the current dam height evaluation index, the seismic resistance evaluation index and the phreatic line height evaluation index, the flood drainage system corresponds to the flood drainage method evaluation index and the flood drainage standard evaluation index, the geological conditions correspond to the foundation structure evaluation index and the terrain slope evaluation index, the meteorological conditions correspond to the rainfall evaluation index, the displacement monitoring corresponds to the surface displacement evaluation index and the internal displacement evaluation index, the safety inspection and archive system correspond to the safety monitoring and early warning evaluation index, and the accident prevention and emergency handling correspond to the emergency rescue plan and drilling evaluation index, the current grade evaluation index, the downstream 1km total number of people evaluation index and the downstream 1km building number evaluation index.

6. The method of claim 5, wherein, The second category label includes human factors, technical factors, environmental factors and management factors. The human factors correspond to the first category label of personnel training and personnel quality, the technical factors correspond to the first category label of tailings properties, stacking system and flood drainage system, the environmental factors correspond to the first category label of geological conditions, meteorological conditions and displacement monitoring, and the management factors correspond to the first category label of safety inspection and archive system and accident prevention and emergency handling.

7. The method of claim 1, wherein, The method further includes: In response to the area risk being higher than a preset risk threshold, a corresponding risk warning is made based on the map.

8. The method of claim 7, wherein, The corresponding risk warning based on the map includes: The target area in the map is highlighted or flickered.

9. The method of claim 7, wherein, The method further comprises: In response to receiving the access request sent by the user based on the risk warning, generating and displaying the region risk information corresponding to the target area, wherein the region risk information comprises at least one of region risk, risk type, risk level, risk index and responsibility subject.

10. A regional risk determination apparatus, characterized by, The device comprises: An index acquisition module is configured to acquire a basic index set of at least one tailings pond in a target region, wherein the basic index set comprises a plurality of basic indexes with first category labels, and each first category label has a corresponding second category label; An index calculation module is configured to calculate the plurality of basic indexes according to the first category label and the second category label corresponding to each basic index in the basic index set, to obtain a risk index of the corresponding tailings pond; A weight determination module is configured to determine a risk weight of each tailings pond in the target region according to the volume of the tailings pond; A region risk determination module is configured to determine a region risk of the target region according to the risk weight and the risk index of each tailings pond; The region risk determination module comprises: A feature parameter determination submodule is configured to calculate the product of the risk index square of each tailings pond in the target region and the risk weight, to obtain a feature parameter of each tailings pond; An index calculation submodule is configured to calculate the square root of the sum of the feature parameters of each tailings pond, to obtain a region risk index of the target region; A region risk determination submodule is configured to determine a region risk of the target region according to the region risk index; The weight determination module comprises: A volume calculation submodule is configured to calculate the volume of each tailings pond in the target region and obtain a region volume; A weight calculation submodule is configured to determine the risk weight of each tailings pond according to the ratio of the volume of each tailings pond to the region volume.

11. An electronic device, comprising: It comprises: A processor; A memory for storing processor-executable instructions; The processor is configured to implement the method of any one of claims 1 to 9 when executing the instructions stored in the memory.

12. A non-transitory computer readable storage medium having stored thereon computer program instructions, wherein, The computer program instructions are executed by the processor to implement the method of any one of claims 1 to 9. The computer program instructions are executed by the processor to implement the method of any one of claims 1 to 9.

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