A cross-region river channel material warehouse site selection method and device and electronic equipment

Abstract

The application discloses a kind of cross-zone riverway material warehouse site selection method, device and electronic equipment, the method comprises: obtaining the original analysis data of multiple river areas of target riverway, original analysis data includes: economic data, population data and dike evaluation data;According to original analysis data, the material reserve index of each river area is calculated respectively;According to the material reserve index corresponding to each river area, the material warehouse address of target riverway is determined from each river area.The application reflects the demand proportion of material warehouse of each administrative district along river by reasonable calculation and analysis, and plans the site selection of material warehouse of cross-zone riverway according to the demand proportion, effectively reduces the randomness of material warehouse construction, so as to quickly respond when drought and flood disasters occur, improve the speed of material transportation and improve the efficiency of rescue.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent analysis, in particular to a cross-region riverway material warehouse site selection method and device and electronic equipment. BACKGROUND

[0002] The material warehouse should be selected in a region with convenient transportation, convenient vehicle passage and water and flood disaster prevention and material transportation, and a site with guaranteed water and electricity conditions. The arrangement of warehouse buildings should be based on the requirements of material storage and transportation and reasonable operation process to ensure rapid material handling. For cross-region riverways, material warehouse site selection has a great influence on rescue efficiency. As to the region near the cross-region riverway, how to layout the material warehouse to maximize the material storage benefit is the current difficulty. In reality, the material warehouse site selection method is usually selected by artificial, which has great randomness, and thus may adversely affect the material allocation efficiency. SUMMARY

[0003] Therefore, the embodiments of the present application provide a cross-region riverway material warehouse site selection method to solve the problem of random material warehouse site selection affecting the material allocation efficiency.

[0004] To achieve the above object, the present application provides the following technical scheme:

[0005] The embodiments of the present application provide a cross-region riverway material warehouse site selection method, comprising:

[0006] Obtaining original analysis data of a plurality of riverway regions along a target riverway, the original analysis data comprising economic data, population data and dike evaluation data;

[0007] Calculating a material reserve index of each riverway region according to the original analysis data;

[0008] Determining a material warehouse address of the target riverway from each riverway region according to the corresponding material reserve index of each riverway region.

[0009] Optionally, the calculating the material reserve index of each riverway region according to the original analysis data comprises:

[0010] Analyzing the original analysis data corresponding to the current riverway region to obtain an economic index, a population index and a flood disaster danger index corresponding to the current riverway region;

[0011] Analyzing the original analysis data corresponding to the current riverway region to obtain a weight coefficient corresponding to the economic index, the population index and the flood disaster danger index corresponding to the current riverway region;

[0012] According to the economic index, population index and flood disaster risk index of the current river area and the corresponding weight coefficients, the material reserve index corresponding to the current river area is calculated.

[0013] Optionally, the analysis of the original analysis data corresponding to the current river area to obtain the economic index, population index and flood disaster risk index corresponding to the current river area comprises:

[0014] The current economic data, current population data and current dike evaluation data are extracted from the original analysis data corresponding to the current river area.

[0015] The current economic data is input into a preset economic evaluation model to obtain the economic index corresponding to the current river area.

[0016] The current population data is input into a preset population evaluation model to obtain the population index corresponding to the current river area.

[0017] The current dike evaluation data is input into a preset flood disaster risk evaluation model to obtain the flood disaster risk index corresponding to the current river area.

[0018] Optionally, the method further comprises:

[0019] The preset economic evaluation model is established based on the relationship between the economic development level and the material reserve demand.

[0020] The preset population evaluation model is established based on the relationship between the population quantity and the material reserve demand.

[0021] The preset flood disaster risk evaluation model is established based on the relationship between the dike evaluation grade and the material reserve demand.

[0022] Optionally, the analysis of the original analysis data corresponding to the current river area to obtain the economic index, population index and flood disaster risk index corresponding to the current river area comprises:

[0023] The original analysis data is standardized to obtain a standardized result.

[0024] The weight coefficients of each evaluation index are obtained by calculating the standardized result by an entropy weight method.

[0025] Optionally, the calculation of the weight coefficients of each evaluation index by the entropy weight method comprises:

[0026] The information entropy of the economic index, population index and flood disaster risk index of the current river area is calculated respectively.

[0027] According to the information entropy, information entropy redundancy of each evaluation index is calculated.

[0028] According to the information entropy redundancy, weight coefficients of each evaluation index are calculated.

[0029] Optionally, the material warehouse address of the target river is determined from the multiple river areas according to the material reserve indexes of the multiple river areas.

[0030] The material reserve indexes of the multiple river areas are compared.

[0031] According to the comparison result, a river area with a larger material reserve index is selected as the material warehouse address.

[0032] The embodiment of the present application further provides a cross-region river material warehouse site selection device, which comprises:

[0033] An acquisition module is configured to acquire original analysis data of multiple river areas of a target river, wherein the original analysis data comprises economic data, population data and dike evaluation data.

[0034] A calculation module is configured to calculate material reserve indexes of the multiple river areas according to the original analysis data.

[0035] A planning module is configured to determine a material warehouse address of the target river from the multiple river areas according to the material reserve indexes of the multiple river areas.

[0036] The embodiment of the present application further provides an electronic device, which comprises:

[0037] A memory and a processor are communicatively connected, and the memory stores computer instructions; the processor executes the computer instructions to perform the cross-region river material warehouse site selection method provided by the embodiment of the present application.

[0038] The embodiment of the present application further provides a computer readable storage medium, which stores computer instructions for making the computer execute the cross-region river material warehouse site selection method provided by the embodiment of the present application.

[0039] The technical scheme of the present application has the following advantages:

[0040] The application provides a cross-region riverway material warehouse site selection method, which comprises the following steps: obtaining original analysis data of a target riverway and a plurality of riverway areas, wherein the original analysis data comprises economic data, population data and dike evaluation data; calculating a material reserve index of each riverway area according to the original analysis data; and determining a material warehouse address of the target riverway from each riverway area according to the corresponding material reserve index of each riverway area. The application reflects the demand proportion of the material warehouse of each administrative area along the river through reasonable calculation and analysis, and plans the material warehouse site selection of the cross-region riverway according to the demand proportion, so that the randomness of the material warehouse construction is effectively reduced, and the response speed of the material transportation is improved, and the rescue efficiency is improved. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0042] Figure 1 The flow chart of the cross-region riverway material warehouse site selection method in the embodiments of the present application;

[0043] Figure 2 The flow chart of calculating the material reserve index of each riverway area according to the original analysis data in the embodiments of the present application;

[0044] Figure 3 The flow chart of analyzing the original analysis data corresponding to the current riverway area in the embodiments of the present application;

[0045] Figure 4 The flow chart of establishing the index model in the embodiments of the present application;

[0046] Figure 5 The flow chart of analyzing the original analysis data corresponding to the current riverway area in the embodiments of the present application;

[0047] Figure 6 The flow chart of calculating the weight coefficient of each evaluation index in the embodiments of the present application;

[0048] Figure 7 The flow chart of determining the material warehouse address of the target riverway in the embodiments of the present application;

[0049] Figure 8 The structural schematic diagram of the cross-region riverway material warehouse site selection device in the embodiments of the present application;

[0050] Figure 9A structural schematic diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0052] According to an embodiment of the present application, a method for selecting a location of a cross-region riverway material warehouse is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0053] In the present embodiment, a method for selecting a location of a cross-region riverway material warehouse is provided, which can be used in the terminal device described above, such as a computer, etc., as shown in the figure, the method for selecting a location of a cross-region riverway material warehouse comprises the following steps: Figure 1

[0054] Step S1: Obtain original analysis data of a plurality of riverway regions along a target riverway, the original analysis data comprising economic data, population data and dike assessment data. Specifically, the economic data is the gross domestic product (GDP) of the administrative region where each riverway city-level material warehouse is located as an evaluation index; the population data is the population quantity of the administrative region where the material warehouse is located; and the dike assessment data is the dike risk assessment result of the administrative region where the material warehouse is located.

[0055] Step S2: Calculate a material reserve index of each riverway region according to the original analysis data. Specifically, the material reserve index obtained by analyzing and calculating the original analysis data can more accurately reflect the demand proportion of the material warehouse of each administrative region along the riverway, thereby improving the accuracy of the location selection.

[0056] Step S3: Determine the location of the material warehouse of the target riverway from each riverway region according to the corresponding material reserve index of each riverway region. Specifically, according to the material reserve index, the demand of the material reserve of each region can be clearly understood. If the reserve index of the region is larger, it means that the material storage quantity of the region is larger relative to other reserve points, which proves that the demand of selecting the region as a city-level material warehouse reserve point is larger. At the same time, by using the material reserve index to determine the location of the material warehouse of the target riverway, the accuracy of the location selection is higher, and it is more in line with the local demand.

[0057] ​Through the steps S1 to S3, the method for selecting the cross-zone riverway material warehouse site provided by the embodiment of the present application reflects the demand proportion of the material warehouse of each administrative zone along the river through reasonable calculation and analysis, and plans the material warehouse site of the cross-zone riverway according to the demand proportion, so as to effectively reduce the randomness of the construction of the material warehouse, and thus to quickly respond to the drought and flood disasters, improve the speed of material transportation, and improve the efficiency of the rescue.

[0058] Specifically, in an embodiment, the step S2 is specifically composed of the following steps as shown in the figure. Figure 2

[0059] The step S21: analyzing the original analysis data corresponding to the current river area to obtain the economic index, the population index and the flood disaster danger index corresponding to the current river area. Specifically, the economic index reflects the influence of the economic development level of the area where the material warehouse is located on the material reserve index. The loss caused by the flood disaster in the economically developed area is higher than that in the economically underdeveloped area, so the corresponding material reserve index should be higher. The population index can reflect the influence of the population on the material reserve index. If the population of the area where the material warehouse is located is larger, the amount of material needed when the flood disaster occurs is larger, and the corresponding flood control material reserve index is higher. The higher the flood disaster danger index is, the higher the loss caused and the wider the rescue range is. Through the analysis of the original analysis data, the economic index, the population index and the flood disaster danger index can be obtained more accurately, which effectively reflects the demand for material reserve in the local area, thereby improving the accuracy of the subsequent site selection.

[0060] The step S22: analyzing the original analysis data corresponding to the current river area to obtain the weight coefficient corresponding to the economic index, the population index and the flood disaster danger index corresponding to the current river area. Specifically,

[0061] The step S23: calculating the material reserve index corresponding to the current river area according to the economic index, the population index and the flood disaster danger index corresponding to the current river area and the weight coefficient corresponding to the economic index, the population index and the flood disaster danger index. Specifically, the material reserve index is determined by the economic index, the population index and the flood disaster danger index of the selected reserve point. The larger the reserve index of the region is, the larger the material storage amount of the region is relative to other reserve points, which proves that the demand for selecting the region as the regional material warehouse reserve point is larger. The formula of the material reserve index is specifically expressed as follows:

[0062] Si=k ei e i '+k pi p i '+k ti η i ',(i=1,2,...,n) ​

[0063] wherein, e i represents the economic index of the i-th along-river region where the material warehouse is located; k ei represents the weight coefficient of the economic index; p i represents the population index of the i-th along-river region where the material warehouse is located; k pi represents the weight coefficient of the population index; η i represents the risk assessment index of the i-th along-river region where the material warehouse is located (weighted average of the river risk assessment index); k ti represents the weight coefficient of the risk assessment index;

[0064] Specifically, in an embodiment, the step S21 described above, as shown in the figure, specifically includes the following steps: Figure 3

[0065] Step S211: extracting the current economic data, the current population data and the current embankment assessment data from the original analysis data corresponding to the current along-river region.

[0066] Step S212: inputting the current economic data into the preset economic evaluation model to obtain the economic index corresponding to the current along-river region. Specifically, the economic index reflects the influence of the economic development level of the region where the along-river region material warehouse is located on the material reserve index. The loss caused by the flood disaster in the economically developed region is higher than that in the economically underdeveloped region, so the corresponding material reserve index should be higher.

[0067] Step S213: inputting the current population data into the preset population evaluation model to obtain the population index corresponding to the current along-river region. Specifically, the population index refers to the influence of the population quantity of the region where the along-river region material warehouse is located on the material reserve index. If the population quantity of the region where the along-river region material warehouse is located is more, the quantity of the material required when the flood disaster occurs is more, and the corresponding flood control material reserve index is higher.

[0068] Step S214: inputting the current embankment assessment data into the preset flood disaster risk evaluation model to obtain the flood disaster risk index corresponding to the current along-river region. Specifically, the flood disaster risk index refers to the embankment risk assessment result of the administrative region where the along-river region material warehouse is located. If the embankment risk assessment result is more dangerous, the loss caused will be higher and the rescue range will be wider, and the corresponding index will be higher.

[0069] Specifically, in an embodiment, the step S21 described above, as shown in the figure, further includes the following steps: Figure 4

[0070] ​​Step S2101: based on the relationship between the economic development level and the demand for material reserves, a preset economic evaluation model is established. Specifically, the economic index reflects the influence of the economic development level of the region where the material warehouse is located on the material reserve index. The loss caused by the flood disaster in the economically developed region is higher than that in the economically underdeveloped region, so the corresponding material reserve index should be higher. In this application, the gross domestic product (GDP) of the administrative region where each river area material warehouse is located is selected as the evaluation index, and the economic index model is constructed as shown below.

[0071]

[0072] wherein e i represents the gross domestic product (GDP) of the administrative region where the i-th river area material warehouse is located, and represents the economic development level of the region.

[0073] Step S2102: based on the relationship between the population quantity and the demand for material reserves, a preset population evaluation model is established. Specifically, the population index refers to the influence of the population quantity of the region where the material warehouse is located on the material reserve index. If the population quantity of the region where the material warehouse is located is larger, the quantity of materials required when the flood disaster occurs is larger, and the corresponding flood control material reserve index is higher. In this application, the population quantity of the administrative region where the material warehouse is located is selected as the evaluation index, and the population quantity of the region where each river area material warehouse is located is measured to construct the population index model as shown below.

[0074]

[0075] wherein p i represents the population quantity of the administrative region where the i-th river area material warehouse is located.

[0076] Step S2103: based on the relationship between the dike evaluation grade and the demand for material reserves, a preset flood disaster danger evaluation model is established. Specifically, the flood disaster danger index refers to the dike risk evaluation result of the region where the material warehouse is located. If the dike risk evaluation result is more dangerous, the loss caused will be higher and the rescue range will be wider, and the corresponding index will be higher. In this application, the dike risk evaluation result of the administrative region where each region material warehouse is located is selected as the evaluation index, and the flood disaster danger index model is constructed as shown below:

[0077]

[0078] wherein η i represents the dike risk evaluation result of the administrative region where the i-th river area material warehouse is located.

[0079] Specifically, in an embodiment, the above step S22, such as Figure 5As shown, specifically comprises the following steps:

[0080] Step S221: standardizing the original analysis data to obtain a standardization result. Specifically, the original analysis data is processed by using the range method, and the processing mode is shown in the following formula:

[0081]

[0082] Step S222: calculating the weight coefficient of each evaluation index by entropy weight method on the standardization result.

[0083] Specifically, by establishing a preset economic evaluation model, a preset population evaluation model and a preset flood disaster risk evaluation model, the original analysis data can be substituted to obtain a more accurate evaluation index, thereby improving the accuracy of site selection. Improving the accuracy of site selection can effectively reduce the randomness of the construction of the material warehouse, thereby quickly responding to the occurrence of drought and flood disasters, improving the speed of material transportation and improving the efficiency of rescue.

[0084] Specifically, in an embodiment, the above step S222, as shown in Figure 6 Specifically comprises the following steps:

[0085] S2221: respectively calculating the information entropy of the economic index, the population index and the flood disaster risk index of the current river area. Specifically, the entropy weight value of the entropy weight method represents the intensity of the evaluation index in the competition. First, a judgment matrix of each evaluation index is constructed; the judgment matrix is normalized to obtain a normalized judgment matrix; the entropy of the evaluation index is determined, and the entropy of the nth index is defined to obtain the entropy weight of the nth index; finally, the weight value is calculated. For example: the proportion of the jth index value of the administrative district where the ith river area material warehouse is located is represented by the following formula:

[0086]

[0087] The information entropy is represented by e j , and the calculation of the information entropy is represented by the following formula:

[0088]

[0089] Wherein: the coefficient ω = lnm.

[0090] S2222: calculating the information entropy redundancy of each evaluation index according to the information entropy. Specifically, for example: the information entropy redundancy is represented by d j , and the calculation of the information entropy redundancy is represented by the following formula:

[0091] d j = 1-e j

[0092] S2223: Calculate the weight coefficient of each evaluation index according to the information entropy redundancy. Specifically, the weight coefficient of each index is represented by k j , and the calculation of the weight coefficient is represented by the following formula:

[0093]

[0094] The weight coefficient k = (k1, k2, …, kn) is obtained by the following formula: n , that is, the weight coefficient of each evaluation index of the material warehouse reserve along the river area: k ei represents the weight coefficient of the economic index, k ei = (k e1 , k e2 , …, k en ); k pi represents the weight coefficient of the population index, k pi = (k p1 , k p2 , …, k pn ); k ti represents the weight coefficient of the flood disaster risk index, k ti = (k t1 , k t2 , …, k tn ).

[0095] Specifically, in an embodiment, the above step S3, as shown in the following, specifically includes the following steps: Figure 7

[0096] Step S31: Compare the material reserve indexes of each river area. Specifically, through comparison, the demand of each area as a material warehouse reserve point can be more clearly reflected.

[0097] Step S32: According to the comparison result, select the river area with a larger material reserve index as the address of the material warehouse. Specifically, if the reserve index of the area is larger, it means that the material storage amount of the area is larger than that of other reserve points, which proves that the demand of selecting the area as a regional material warehouse reserve point is greater.

[0098] In this embodiment, a cross-regional river material warehouse site selection device is also provided, which is used to implement the above embodiments and preferred embodiments, and has been described above. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware is also possible and is contemplated.

[0099] The present embodiment provides a cross-regional river material warehouse site selection device, as shown in the following, which comprises: Figure 8 ​​

[0100] The acquisition module 101 is used to acquire raw analysis data from multiple riverside areas along the target river. The raw analysis data includes economic data, population data, and levee assessment data. For details, please refer to the relevant description of step S1 in the above method embodiment, which will not be repeated here.

[0101] The calculation module 102 is used to calculate the material reserve index of each riverside region based on the original analysis data. For details, please refer to the relevant description of step S2 in the above method embodiment, which will not be repeated here.

[0102] The planning module 103 determines the material warehouse address of the target river channel from each riverside region based on the corresponding material reserve index. For details, please refer to the relevant description of step S3 in the above method embodiment, which will not be repeated here.

[0103] In this embodiment, the cross-regional river material warehouse site selection device is presented in the form of a functional unit. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0104] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0105] According to embodiments of the present invention, an electronic device is also provided, such as... Figure 9 As shown, the electronic device may include a processor 901 and a memory 902, wherein the processor 901 and the memory 902 may be connected via a bus or other means. Figure 9 Taking the example of a connection between China and Israel via a bus.

[0106] Processor 901 can be a Central Processing Unit (CPU). Processor 901 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0107] The memory 902, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the methods in the method embodiments of the present application. The processor 901 performs various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 902, that is, implements the methods in the above method embodiments.

[0108] The memory 902 can include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required by a function; the data storage area can store data created by the processor 901 and the like. In addition, the memory 902 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory 902 can optionally include a memory disposed remotely with respect to the processor 901, which can be connected to the processor 901 through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0109] One or more modules are stored in the memory 902, and when executed by the processor 901, the methods in the above method embodiments are performed.

[0110] The above electronic device specific details can be understood in correspondence with the above method embodiments corresponding to the relevant description and effects, which will not be described here.

[0111] Those skilled in the art can understand that all or part of the processes in the above method embodiments can be completed by a computer program instructing related hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid state drive (SSD), etc. The storage medium can also include a combination of the above types of memories.

[0112] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method for selecting a site for a cross-region riverway material warehouse, characterized by, The method comprises the following steps: obtaining original analysis data of a plurality of river areas along a target river, wherein the original analysis data comprises economic data, population data and dike assessment data; analyzing the original analysis data corresponding to the current river area to obtain economic indexes, population indexes and flood disaster risk indexes corresponding to the current river area; analyzing the original analysis data corresponding to the current river area to obtain weight coefficients corresponding to the economic indexes, the population indexes and the flood disaster risk indexes of the current river area; the method comprises the following steps: standardizing the original analysis data by using a range method to obtain a standardization result; and calculating the weight coefficients of each evaluation index by using an entropy weight method based on the standardization result; calculating a material reserve index corresponding to the current river area according to the economic indexes, the population indexes and the flood disaster risk indexes of the current river area and the weight coefficients corresponding to the economic indexes, the population indexes and the flood disaster risk indexes; determining a material warehouse address of the target river from each river area according to the material reserve indexes corresponding to each river area; comparing the material reserve indexes corresponding to each river area, and screening a river area with a larger material reserve index as the address of the material warehouse according to a comparison result; the method comprises the following steps: extracting current economic data, current population data and current dike assessment data from the original analysis data corresponding to the current river area; inputting the current economic data into a preset economic evaluation model to obtain the economic indexes corresponding to the current river area; inputting the current population data into a preset population evaluation model to obtain the population indexes corresponding to the current river area; inputting the current dike assessment data into a preset flood disaster risk evaluation model to obtain the flood disaster risk indexes corresponding to the current river area; the method further comprises the following steps: establishing the preset economic evaluation model based on the relationship between the economic development level and the material reserve demand; establishing the preset population evaluation model based on the relationship between the population quantity and the material reserve demand; establishing the preset flood disaster risk evaluation model based on the relationship between the dike assessment grade and the material reserve demand.

2. The method of claim 1, wherein, the method comprises the following steps: calculating the information entropy of the economic indexes, the population indexes and the flood disaster risk indexes of the current river area respectively; calculating the information entropy redundancy of each evaluation index according to the information entropy; calculating the weight coefficients of each evaluation index according to the information entropy redundancy.

3. A site selection device for cross-regional river material warehouses, characterized in that, The method comprises the following steps: an acquisition module: obtaining original analysis data of a plurality of river areas along a target river, wherein the original analysis data comprises economic data, population data and dike assessment data; The computing module: analyzing the original analysis data corresponding to the current river area to obtain the economic index, population index and flood disaster risk index corresponding to the current river area; analyzing the original analysis data corresponding to the current river area to obtain the weight coefficients corresponding to the economic index, population index and flood disaster risk index of the current river area; including: using the range method to standardize the original analysis data to obtain the standardization result; calculating the standardization result by the entropy weight method to obtain the weight coefficients of each evaluation index; calculating the material reserve index corresponding to the current river area according to the economic index, population index and flood disaster risk index of the current river area and the weight coefficients corresponding thereto; The planning module: determining the material warehouse address of the target river from each river area according to the material reserve index corresponding to each river area; The site selection module: comparing the material reserve indexes corresponding to each river area, and selecting the river area with a larger material reserve index as the address of the material warehouse according to the comparison result; The computing module is further used for: extracting the current economic data, current population data and current dike evaluation data from the original analysis data corresponding to the current river area; inputting the current economic data into a preset economic evaluation model to obtain the economic index corresponding to the current river area; inputting the current population data into a preset population evaluation model to obtain the population index corresponding to the current river area; inputting the current dike evaluation data into a preset flood disaster risk evaluation model to obtain the flood disaster risk index corresponding to the current river area; The device further includes a model establishing module for: establishing the preset economic evaluation model based on the relationship between economic development level and material reserve demand; establishing the preset population evaluation model based on the relationship between population quantity and material reserve demand; establishing the preset flood disaster risk evaluation model based on the relationship between dike evaluation grade and material reserve demand.

4. An electronic device, comprising: including: a memory and a processor, which are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the cross-region river material warehouse site selection method of any one of claims 1 or 2.

5. A computer readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing the computer to perform the cross-region river material warehouse site selection method of any one of claims 1 or 2.

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