Decision scheduling method, system and equipment for hydraulic engineering and medium

Abstract

The invention discloses a decision scheduling method, system and device for a water conservancy project and a medium, and the method comprises the steps: obtaining a plurality of water conservancy scheduling schemes of the water conservancy project; performing water conservancy rehearsal on all the water conservancy scheduling schemes to obtain rehearsal data of each water conservancy scheduling scheme; according to all the rehearsal data, all the water conservancy scheduling schemes are subjected to sequence division, a scheme sequence set is obtained, the scheme sequence set comprises a plurality of water conservancy sequences, and each water conservancy sequence corresponds to one scheme sequence in all the water conservancy scheduling schemes; and performing consistency scheduling decision on all the water conservancy sequences in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project. The method can effectively improve the adaptation degree of water conservancy decision scheduling to the actual water conservancy disaster process, and is beneficial to improving the water conservancy scheduling effect.

Description

Technical Field

[0001] The present invention relates to the field of hydrological science and technology, and in particular to a method, system, equipment and medium for dispatching a water conservancy project. Background Art

[0002] When facing the risks of water disasters such as floods, rainstorms, etc., the decision-making and scheduling of water conservancy projects have attracted much attention because they can minimize the disaster losses caused by water disasters to the affected river basins through systematic planning and emergency measures.

[0003] At present, the relevant technology usually establishes a pre-storage and pre-discharge risk decision model for water conservancy projects, then inputs the actual water disaster process data set into the pre-storage and pre-discharge risk decision model, and dispatches the water conservancy project through a single water conservancy scheduling plan determined by the pre-storage and pre-discharge risk decision model; however, since the water conservancy disaster process is not uniform in time and space distribution, for example, there are differences in flood peaks and troughs during flood disasters, the final water conservancy scheduling plan determined by this method cannot adapt well to the actual water conservancy disaster process, and the water conservancy scheduling effect is unsatisfactory.

[0004] Therefore, the problems existing in related technologies still need to be solved and optimized urgently. Summary of the Invention

[0005] The purpose of the present invention is to solve one of the technical problems existing in the related art to at least a certain extent.

[0006] To this end, one purpose of an embodiment of the present invention is to provide a decision-making and scheduling method, system, equipment and medium for water conservancy projects, wherein the method can effectively improve the adaptability of water conservancy decision-making and scheduling to actual water conservancy disaster processes, which is conducive to improving the water conservancy scheduling effect.

[0007] In order to achieve the above technical objectives, the technical solutions adopted in the embodiments of the present application include:

[0008] In a first aspect, an embodiment of the present application provides a decision-making and scheduling method for a water conservancy project, comprising:

[0009] Obtain several water conservancy scheduling plans for water conservancy projects;

[0010] Performing a water conservancy preview on all the water conservancy scheduling plans to obtain preview data for each of the water conservancy scheduling plans;

[0011] According to all the preview data, all the water conservancy scheduling schemes are divided into order to obtain a scheme order set, wherein the scheme order set includes a plurality of water conservancy orders, and each water conservancy order corresponds to one of the scheme rankings of all the water conservancy scheduling schemes;

[0012] A consistent scheduling decision is made on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project.

[0013] In addition, the method according to the above embodiment of the present application may also have the following additional technical features:

[0014] Furthermore, in one embodiment of the present application, the obtaining of several water conservancy scheduling plans for a water conservancy project includes:

[0015] Obtaining a pre-trained language model and a water conservancy goal of the water conservancy project;

[0016] Conducting consensus decision-making on the water conservancy goal through a number of different decision-makers, and obtaining consensus decision information corresponding to all the decision-makers;

[0017] The consensus decision information is input into the pre-trained language model for solution analysis and extraction to obtain a plurality of water conservancy scheduling solutions.

[0018] Furthermore, in one embodiment of the present application, all the water conservancy scheduling plans are divided into order according to all the preview data to obtain a plan order set, including:

[0019] Obtaining a number of decision bodies corresponding to all the water conservancy scheduling plans;

[0020] Based on all the preview data, all the decision-makers are evaluated for indicators to obtain a decision matrix for each decision-maker, wherein the decision matrix includes a plurality of matrix elements, each of which is used to indicate an indicator evaluation value of the decision-maker for the corresponding water conservancy scheduling plan;

[0021] According to all the decision matrices, all the water conservancy scheduling plans are sorted to obtain the plan order set.

[0022] Furthermore, in one embodiment of the present application, the index evaluation is performed on all the decision bodies based on all the preview data to obtain a decision matrix for each decision body, including:

[0023] Obtaining a pre-trained language model and an indicator prompt word template, as well as attribute information of the decision body;

[0024] Constructing an indicator prompt word according to the indicator prompt word template and the attribute information;

[0025] Inputting the indicator prompt into the pre-trained language model to generate indicators, and obtaining an evaluation indicator table for the decision body;

[0026] According to the evaluation index table, the preview data is subjected to index analysis to obtain the decision matrix.

[0027] Furthermore, in one embodiment of the present application, all the water conservancy scheduling schemes are sorted according to all the decision matrices to obtain the scheme order set, including:

[0028] Performing matrix normalization on the decision matrix to obtain a normalized matrix;

[0029] According to all the water conservancy scheduling plans, performing distance analysis on the normalized matrix to obtain a plan distance of each of the water conservancy scheduling plans;

[0030] According to the distances of all the schemes, all the water conservancy scheduling schemes are sorted by distance to obtain the water conservancy order.

[0031] Furthermore, in one embodiment of the present application, the solution distance includes a positive solution distance and a negative solution distance. The distance analysis is performed on the normalized matrix according to all the water conservancy scheduling solutions to obtain the solution distance of each water conservancy scheduling solution, including:

[0032] Performing weighted normalization on the normalized matrix to obtain a weighted normalized matrix;

[0033] According to the water conservancy scheduling plan, an ideal solution calculation is performed on the weighted normalized matrix to obtain a positive ideal solution and a negative ideal solution;

[0034] According to the positive ideal solution and the negative ideal solution, distance calculation is performed on the weighted normalization matrix to obtain the positive solution distance and the negative solution distance.

[0035] Furthermore, in one embodiment of the present application, performing a consistent scheduling decision on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project includes:

[0036] Obtaining a plurality of decision bodies corresponding to the scheme order set;

[0037] Performing a local order expectation analysis on each water conservancy order according to all the decision bodies to obtain a plurality of first expected values, wherein the first expected values are used to represent the expected value of a single decision body for the corresponding water conservancy order;

[0038] Performing a global order expectation analysis on all the water conservancy orders according to all the decision bodies to obtain a plurality of second expected values, wherein the second expected values are used to represent the expected values of all the decision bodies for the corresponding water conservancy orders;

[0039] Based on all the first expected values and all the second expected values, all the water conservancy orders are screened for consistency decisions to obtain water conservancy scheduling information of the water conservancy project.

[0040] In a second aspect, an embodiment of the present application provides a decision-making and scheduling system for a water conservancy project, including:

[0041] The first processing unit is used to obtain several water conservancy scheduling plans for the water conservancy project;

[0042] A second processing unit is configured to perform a water conservancy preview on all the water conservancy scheduling plans to obtain preview data for each of the water conservancy scheduling plans;

[0043] a third processing unit, configured to rank all the water conservancy scheduling schemes according to all the preview data to obtain a scheme order set, wherein the scheme order set includes a plurality of water conservancy orders, each of which corresponds to one of the scheme rankings of all the water conservancy scheduling schemes;

[0044] The fourth processing unit performs a consistent scheduling decision on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project.

[0045] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0046] at least one processor;

[0047] at least one memory for storing at least one program;

[0048] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0049] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a program executable by a processor, and the program executable by the processor is used to implement the above method when executed by the processor.

[0050] The advantages and benefits of this application will be partially given in the following description, and partially become apparent from the following description, or learned through practice of this application:

[0051] The embodiment of the present application discloses a decision-making and scheduling method, system, equipment and medium for a water conservancy project, wherein the method obtains several water conservancy scheduling schemes for the water conservancy project; performs water conservancy preview on all the water conservancy scheduling schemes to obtain preview data for each of the water conservancy scheduling schemes; according to all the preview data, all the water conservancy scheduling schemes are sorted to obtain a scheme sequence set, wherein the scheme sequence set includes several water conservancy orders, each of the water conservancy orders corresponds to one of the schemes in all the water conservancy scheduling schemes; performs a consistent scheduling decision on all the water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information for the water conservancy project. The method sorts all the water conservancy scheduling schemes to obtain a scheme sequence set, and performs a consistent scheduling decision on the scheme sequence set, which can screen out the optimal water conservancy order (i.e., water conservancy scheduling information) among all the water conservancy orders. The water conservancy scheduling information can better adapt to the actual water conservancy disaster process and effectively improve the water conservancy scheduling effect of the water conservancy project during the water conservancy disaster process. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following introduction is made to the drawings of the embodiments of the present application or the related technical solutions in the prior art. It should be understood that the drawings introduced below are only for the convenience of clearly expressing some embodiments of the technical solutions of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative work.

[0053] Figure 1 A flowchart of a decision-making and scheduling method for a water conservancy project provided in an embodiment of the present application;

[0054] Figure 2 A schematic diagram of the structural framework of a water conservancy project decision-making and scheduling system provided in an embodiment of the present application;

[0055] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and are not to be construed as limiting the present application. For the step numbers in the following embodiments, they are provided only for the convenience of explanation and are not intended to limit the order of the steps. The order of execution of the steps in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0058] At present, the relevant technology usually establishes a pre-storage and pre-discharge risk decision model for water conservancy projects, then inputs the actual water disaster process data set into the pre-storage and pre-discharge risk decision model, and dispatches the water conservancy project through a single water conservancy scheduling plan determined by the pre-storage and pre-discharge risk decision model; however, since the water conservancy disaster process is not uniform in time and space distribution, for example, there are differences in flood peaks and troughs during flood disasters, the final water conservancy scheduling plan determined by this method cannot adapt well to the actual water conservancy disaster process, and the water conservancy scheduling effect is unsatisfactory.

[0059] In addition, there are related techniques for determining water conservancy scheduling plans through group decision-making by expert groups. Specific group decision-making methods include the Delphi method, the Nominal Group Technique (NGT), the Stepladder Technique, and the Consensus Decision-Making method. These related techniques typically require each expert in the expert group to score different plans and determine the water conservancy scheduling plan with the highest score as the final water conservancy scheduling plan. However, since each expert in the expert group has their own areas of expertise, individual blind spots in their understanding may have an adverse impact on the decision-making process. The final water conservancy scheduling plan determined by these techniques is highly subjective and lacks objectivity. Furthermore, the final water conservancy scheduling plan determined by these related techniques is not easily interpretable and often does not fully consider the opinions of all experts in the expert group, making the final water conservancy scheduling plan incomplete.

[0060] It should be noted that the aforementioned related technologies are only used to assist in understanding the technical solutions of this application and do not mean that they belong to the disclosed prior art.

[0061] In view of this, an embodiment of the present application provides a decision-making and scheduling method, system, equipment and medium for water conservancy projects, wherein the method divides all water conservancy scheduling schemes into order to obtain a scheme order set, and makes consistent scheduling decisions on the scheme order set. It can screen out the optimal water conservancy order (i.e., water conservancy scheduling information) among all water conservancy orders. The water conservancy scheduling information can better adapt to the actual water conservancy disaster process and effectively improve the water conservancy scheduling effect of water conservancy projects during water conservancy disasters.

[0062] In addition, this method divides the water conservancy scheduling plans into orders, specifically by dividing the water conservancy order corresponding to each decision-making body based on the decision matrix of each decision-making body, and making consistent scheduling decisions on the water conservancy order corresponding to each decision-making body. It can comprehensively consider all water conservancy orders and fully consider the role of all decision-making bodies in decision-making and scheduling, thereby making the final water conservancy scheduling information highly objective and interpretable, which is conducive to improving the water conservancy scheduling effect.

[0063] Reference Figure 1 In an embodiment of the present application, a decision-making and scheduling method for a water conservancy project includes:

[0064] Step 110: obtaining several water conservancy scheduling plans for water conservancy projects;

[0065] In the embodiments of this application, water conservancy projects may include flood control projects, water resource allocation projects, hydropower generation projects, and the like. Specifically, these water conservancy projects may include reservoirs, dams, flood diversion channels, hydropower stations, and the like. For a particular water conservancy project, its water conservancy scheduling plan may be the scheduling plan that the water conservancy project implements to achieve efficient water resource utilization and disaster prevention and control. Specifically, for flood disasters, the water conservancy scheduling plan for the water conservancy project may be a flood control scheduling plan, which may specifically include flood detention, flow discharge, and the like. This application does not impose any restrictions on water conservancy scheduling plans.

[0066] In some embodiments, obtaining several water conservancy scheduling plans for a water conservancy project includes:

[0067] Obtaining a pre-trained language model and a water conservancy goal of the water conservancy project;

[0068] Conducting consensus decision-making on the water conservancy goal through a number of different decision-makers, and obtaining consensus decision information corresponding to all the decision-makers;

[0069] The consensus decision information is input into the pre-trained language model for solution analysis and extraction to obtain a plurality of water conservancy scheduling solutions.

[0070] In an embodiment of the present application, the pre-trained language model can be a large language model (LLM) constructed based on deep learning technology; the water conservancy target can be a water resource scheduling target of a water conservancy project, such as the water resource scheduling target of "how much flood water should be discharged by the water conservancy project in the emergency scheduling of floods in a certain river basin".

[0071] It can be understood that the decision-making body can be at least one of an AI intelligent body, an expert, etc. The embodiment of the present application takes the example that all decision-making bodies are AI intelligent bodies. Each decision-making body is trained based on a different field database. For example, the first decision-making body can be trained based on a reservoir scheduling field database, the second decision-making body can be trained based on a flood control field database, the third decision-making body can be trained based on a hydropower generation field database, and the fourth decision-making body can be trained based on a hydrological ecology field database. The examples of decision-making bodies in this application are only for illustration and do not limit this application. For example, decision-making bodies can also be trained based on data sets in the fields of water supply, shipping, etc.

[0072] In practical applications, several decision-makers who make consensus decisions on water conservancy goals can be determined based on the semantic similarity between the descriptive information of each decision-maker (such as the domain of the decision-maker, etc.) and the water conservancy goals. Specifically, the semantic similarity between each decision-maker and the water conservancy goals is sorted, and then several decision-makers with higher semantic similarity are used as the decision-makers for consensus decision-making.

[0073] It should be noted that consensus decision-making can be achieved by group decision-making on water conservancy goals by several different decision-makers, thereby obtaining consensus decision information. This consensus decision information records the group decision discussion information of several water conservancy scheduling plans, and at least one decision-maker considers each water conservancy scheduling plan feasible. After obtaining the consensus decision information, it can be input into a pre-trained language model. The pre-trained language model can then extract and classify the group decision discussion information in the consensus decision information, thereby deriving several water conservancy scheduling plans.

[0074] Step 120: Perform a water conservancy preview on all the water conservancy scheduling plans to obtain preview data for each water conservancy scheduling plan;

[0075] In an embodiment of the present application, each water conservancy scheduling plan can be input into the digital twin water conservancy platform for water conservancy preview, so as to obtain the scheduling data after the simulated scheduling of each water conservancy scheduling plan, which is recorded as preview data.

[0076] Step 130: Based on all the preview data, all the water conservancy scheduling schemes are ranked to obtain a scheme order set, wherein the scheme order set includes a plurality of water conservancy orders, each of which corresponds to one of the scheme rankings of all the water conservancy scheduling schemes;

[0077] In an embodiment of the present application, all water conservancy scheduling schemes can be combined and sorted based on the preview data of each water conservancy scheduling scheme to obtain a scheme order set consisting of several water conservancy orders, and each water conservancy order corresponds to one of the scheme orders of all water conservancy scheduling schemes.

[0078] For example, if the total number of water conservancy scheduling plans is 3, they are d1: no flood discharge, d2: discharge 9000m 3 / s and d3: discharge 11000m 3 / s; the obtained scheme order set can have 5 water conservancy orders, among which the first water conservancy order can be {d1, d2, d3}; the second water conservancy order can be {d2, d1, d3}; the third water conservancy order can be {d2, d3, d1}; the fourth water conservancy order can be {d3, d2, d1}; the fifth water conservancy order can be {d3, d1, d2}. This application example is for illustration only.

[0079] In some embodiments, all the water conservancy scheduling plans are divided into order according to all the preview data to obtain a plan order set, including:

[0080] Obtaining a number of decision bodies corresponding to all the water conservancy scheduling plans;

[0081] Based on all the preview data, all the decision-makers are evaluated for indicators to obtain a decision matrix for each decision-maker, wherein the decision matrix includes a plurality of matrix elements, each of which is used to indicate an indicator evaluation value of the decision-maker for the corresponding water conservancy scheduling plan;

[0082] Furthermore, the index evaluation is performed on all the decision bodies based on all the preview data to obtain a decision matrix for each decision body, including:

[0083] Obtaining a pre-trained language model and an indicator prompt word template, as well as attribute information of the decision body;

[0084] Constructing an indicator prompt word according to the indicator prompt word template and the attribute information;

[0085] Inputting the indicator prompt into the pre-trained language model to generate indicators, and obtaining an evaluation indicator table for the decision body;

[0086] According to the evaluation index table, the preview data is subjected to index analysis to obtain the decision matrix.

[0087] In this embodiment, since each decision-maker is trained based on a different domain database, each decision-maker has a distinct area of expertise, recorded as attribute information, that differs from the others. Sequential partitioning can first be performed based on each decision-maker's attribute information and all pre-trained data to determine a decision matrix corresponding to each decision-maker's attribute information. This attribute information records the decision-maker's domain, professional characteristics, and key dimensions to be considered.

[0088] It is understandable that the indicator prompt word template is used to instruct the pre-trained language model to generate an evaluation indicator system corresponding to each decision body. There are many specific implementation methods of the indicator prompt word template. For example, "As an expert in {field}, you need to evaluate the plan from {key dimension list}, focus on {professional characteristics}, generate quantifiable indicators, and consider factors such as evidence sufficiency, data integrity, and logical rigor." This application example is for illustrative purposes only.

[0089] For a certain decision body, the attribute information of the decision body can be input into the indicator prompt word template to obtain the indicator prompt; then, the indicator prompt is input into the pre-trained language model, and the evaluation index table of the decision body is generated through the pre-trained language model. The evaluation index table includes several evaluation indicators that are adaptively matched with the decision prompt.

[0090] After determining the evaluation index table of the decision body, an anchor standard word corresponding to each evaluation indicator in the evaluation index table can be constructed. Then, based on the Schema-LLM technology, the preview data of each water conservancy scheduling plan is matched to the corresponding evaluation indicator in the evaluation index table. By calculating the semantic similarity between the anchor standard word of each evaluation indicator and the scheduling plan description corresponding to the preview data, the index evaluation value of the preview data of each water conservancy scheduling plan on each evaluation indicator in the evaluation index table is determined. Based on all the indicator evaluation values, the decision matrix of the decision body can be obtained. The decision matrices of the other decision bodies are similar, and can be simply deduced by analogy. This application will not go into details here.

[0091] For example, the decision matrix of a decision body can be expressed as:

[0092]

[0093] Among them, A i is the decision matrix of the i-th decision body; is the evaluation value of the nth evaluation indicator of the mth water conservancy scheduling scheme by the i-th decision-maker; M is the total number of water conservancy scheduling schemes; N is the total number of evaluation indicators in the evaluation indicator table of the i-th decision-maker.

[0094] According to all the decision matrices, all the water conservancy scheduling plans are sorted to obtain the plan order set.

[0095] Furthermore, all the water conservancy scheduling schemes are sorted according to all the decision matrices to obtain the scheme order set, including:

[0096] Performing matrix normalization on the decision matrix to obtain a normalized matrix;

[0097] In the embodiment of the present application, for any decision matrix among all decision matrices, matrixing may be performing normalization processing on the decision matrix to obtain a normalized matrix after eliminating the dimension effect.

[0098] According to all the water conservancy scheduling plans, performing distance analysis on the normalized matrix to obtain a plan distance of each of the water conservancy scheduling plans;

[0099] The solution distance includes a positive solution distance and a negative solution distance. The distance analysis is performed on the normalized matrix based on all the water conservancy scheduling solutions to obtain the solution distance of each water conservancy scheduling solution, including:

[0100] Performing weighted normalization on the normalized matrix to obtain a weighted normalized matrix;

[0101] According to the water conservancy scheduling plan, an ideal solution calculation is performed on the weighted normalized matrix to obtain a positive ideal solution and a negative ideal solution;

[0102] According to the positive ideal solution and the negative ideal solution, distance calculation is performed on the weighted normalization matrix to obtain the positive solution distance and the negative solution distance.

[0103] In an embodiment of the present application, weighted normalization can first obtain the indicator weight corresponding to each matrix element in the normalized matrix, and perform weighted normalization on the normalized matrix based on all indicator weights to obtain a weighted normalized matrix, wherein the indicator weight corresponding to each matrix element can be generated by the pre-trained language model when the pre-trained language model generates an evaluation indicator table.

[0104] It is understandable that, for the i-th decision body and the m-th water conservancy scheduling scheme, the ideal solution calculation can be based on the ideal point method to calculate the positive ideal solution and the negative ideal solution of the m-th water conservancy scheduling scheme for the i-th decision body. Specifically, the embodiment of the present application can obtain the optimal value of each matrix element in the weighted normalized matrix based on the ideal point method, and determine all optimal values as positive ideal solutions, and obtain the worst value of each matrix element in the weighted normalized matrix, and determine all worst values as negative ideal solutions.

[0105] It should be noted that the distance calculation can be to calculate the distance between the positive ideal solution and the weighted normalized matrix respectively to obtain the positive solution distance of the i-th decision body to the m-th water conservancy scheduling scheme, and to calculate the distance between the negative ideal solution and the weighted normalized matrix to obtain the negative solution distance of the i-th decision body to the m-th water conservancy scheduling scheme.

[0106] For example, the correct solution distance of the i-th decision-maker to the m-th water conservancy scheduling scheme can be expressed as:

[0107]

[0108] in, is the correct solution distance of the i-th decision-maker to the m-th water conservancy scheduling plan; is the value of the nth matrix element of the mth water conservancy scheduling plan in the weighted normalized matrix of the i-th decision-maker; is the optimal value of the nth matrix element of the mth water conservancy scheduling plan in the weighted standardized matrix of the i-th decision-maker.

[0109] It is worth mentioning that since the weighted normalization matrix is obtained based on the decision matrix, It can also be the weighted standard value of the nth evaluation index of the mth water conservancy scheduling plan by the i-th decision-maker, and the weighted standard value refers to the index evaluation value after weighted standardization. And, It can be the nth optimal value in the positive ideal solution of the mth water conservancy scheduling plan for the i-th decision-maker.

[0110] It should be noted that the negative solution distance between the i-th decision-maker and the m-th water conservancy scheduling solution is similar to the positive solution distance between the i-th decision-maker and the m-th water conservancy scheduling solution, and can be simply deduced. In addition, the solution distances between the remaining decision-makers and the remaining water conservancy scheduling solutions are also similar to the solution distance between the i-th decision-maker and the m-th water conservancy scheduling solution, and can be simply deduced. This application will not elaborate on this.

[0111] According to the distances of all the schemes, all the water conservancy scheduling schemes are sorted by distance to obtain the water conservancy order.

[0112] In an embodiment of the present application, for the water conservancy order of the i-th decision body, the relative proximity of the i-th decision body to each water conservancy scheduling plan can be calculated based on the plan distance of the i-th decision body to each water conservancy scheduling plan, and the water conservancy order of all water conservancy scheduling plans for the i-th decision body can be determined based on the size relationship of all relative proximities.

[0113] For example, the relative closeness of the i-th decision-maker to the m-th water conservancy scheduling plan can be expressed as:

[0114]

[0115] in, is the relative closeness of the i-th decision-maker to the m-th water conservancy scheduling plan; is the negative solution distance of the i-th decision-maker to the m-th water conservancy scheduling plan.

[0116] It can be understood that after obtaining the relative proximity of the i-th decision-maker to all water conservancy scheduling plans, the relative proximity can be sorted from large to small, and based on the sorting, each relative proximity can be mapped to the corresponding water conservancy scheduling plan, thereby obtaining the water conservancy order of all water conservancy scheduling plans for the i-th decision-maker; the water conservancy order of the remaining decision-makers is the same and can be simply deduced by analogy.

[0117] Step 140: Perform consistency scheduling decisions on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project.

[0118] In an embodiment of the present application, after obtaining the scheme sequence set, a consistent scheduling decision can be made for all water conservancy sequences to screen out the optimal water conservancy sequence among all water conservancy sequences, and the optimal water conservancy sequence is determined as the water conservancy scheduling information of the water conservancy project.

[0119] It should be noted that, for the sake of ease of understanding, the water conservancy scheduling schemes d1, d2 and d3 mentioned above are simple examples. In actual application, d1 can specifically mean not discharging flood water within a certain period of time; d2 can mean discharging water at a rate of 9000m3 within a certain period of time. 3 / s flood discharge; and d3 can be within a certain period of time, at a rate of 11000m 3 / s of flood discharge flow is used for discharge.

[0120] In some embodiments, performing consistent scheduling decisions on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project includes:

[0121] Obtaining a plurality of decision bodies corresponding to the scheme order set;

[0122] Performing a local order expectation analysis on each water conservancy order according to all the decision bodies to obtain a plurality of first expected values, wherein the first expected values are used to represent the expected value of a single decision body for the corresponding water conservancy order;

[0123] Performing a global order expectation analysis on all the water conservancy orders according to all the decision bodies to obtain a plurality of second expected values, wherein the second expected values are used to represent the expected values of all the decision bodies for the corresponding water conservancy orders;

[0124] Based on all the first expected values and all the second expected values, all the water conservancy orders are screened for consistency decisions to obtain water conservancy scheduling information of the water conservancy project.

[0125] In the embodiment of the present application, for any decision body of all decision weights, the local order expectation analysis can be performed by separately calculating the expected value of the decision body for each water conservancy order, thereby obtaining the expected value of the decision body for each water conservancy order, which is recorded as the first expected value. The total number of the first expected values is equal to the product of the total number of decision bodies and the total number of water conservancy orders. The global order expectation analysis can be performed by separately calculating the expected value of all decision bodies for each water conservancy order, which is recorded as the second expected value. The total number of the second expected values is equal to the total number of water conservancy orders.

[0126] It can be understood that in the first embodiment, the optimal water conservancy order can be obtained by solving the consistency decision function based on all the first expected values and all the second expected values, and the water conservancy order with the highest decision consistency is used as the optimal water conservancy order, thereby obtaining the water conservancy scheduling information of the water conservancy project. The consistency decision function of the first embodiment can be expressed as:

[0127]

[0128] Among them, max(·) is the maximum value function; EDCD is the consistency decision function; E(c m ) is the second expected value of all decision-makers for the mth water conservancy order; c im is the first expected value of the i-th decision-maker for the m-th water conservancy order; G is the total number of decision proposals; c′ m is the variable that needs to be solved, which is the water conservancy order with the highest decision consistency.

[0129] It should be noted that in the second embodiment, the decision weight of each decision body can be obtained first. The decision weight of each decision body is positively correlated with the semantic similarity between the aforementioned descriptive information and the water conservancy target. For example, for a certain decision body, the greater the semantic similarity between the descriptive information of the decision body and the water conservancy target, the greater the decision weight of the decision body; otherwise, the smaller the decision weight. Then, based on all decision weights, all first expected values, and all second expected values, the optimal water conservancy order is obtained by solving the consistency decision function. The consistency decision function of the second embodiment can be expressed as:

[0130]

[0131] Among them, ψ i is the decision weight of the i-th decision maker.

[0132] A decision-making and scheduling system for a water conservancy project proposed according to an embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0133] Reference Figure 2 , a decision-making and scheduling system for a water conservancy project proposed in an embodiment of the present application includes:

[0134] The first processing unit 101 is used to obtain several water conservancy scheduling plans for water conservancy projects;

[0135] The second processing unit 102 is configured to perform a water conservancy preview on all the water conservancy scheduling plans to obtain preview data for each of the water conservancy scheduling plans;

[0136] The third processing unit 103 is configured to rank all the water conservancy scheduling schemes according to all the preview data to obtain a scheme order set, wherein the scheme order set includes a plurality of water conservancy orders, each of which corresponds to one of the scheme rankings of all the water conservancy scheduling schemes;

[0137] The fourth processing unit 104 is configured to perform a consistent scheduling decision on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project.

[0138] Reference Figure 3 , an embodiment of the present application further provides an electronic device, including:

[0139] at least one processor 201;

[0140] At least one memory 202, configured to store at least one program;

[0141] When the at least one program is executed by the at least one processor 201 , the at least one processor 201 implements the above method embodiment.

[0142] Similarly, it can be understood that the contents of the above method embodiments are applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0143] An embodiment of the present application further provides a computer-readable storage medium, in which a program executable by the processor 201 is stored. The program executable by the processor 201 is used to implement the above-mentioned method embodiment when executed by the processor 201.

[0144] Similarly, the contents of the above method embodiments are applicable to the computer-readable storage medium embodiments. The functions specifically implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0145] In some optional embodiments, the functions / operations mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the functions / operations involved, the two boxes shown in succession may actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiments presented and described in the flow chart of the present application are provided in an exemplary manner for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operations and logic flows presented herein. Optional embodiments are contemplated in which the order of the various operations is changed and the sub-operations described as a part of a larger operation are performed independently.

[0146] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present application. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the routine skills of an engineer. Therefore, a person skilled in the art can implement the present application as set forth in the claims using ordinary techniques without undue experimentation. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the appended claims and their equivalents.

[0147] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the embodiment method of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0148] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0149] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0150] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0151] In the above description of this specification, reference to the terms "one embodiment / example," "another embodiment / example," or "certain embodiments / examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples.

[0152] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and intent of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0153] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present application, and these equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A decision-making and scheduling method for a water conservancy project, characterized in that: include: Obtain several water conservancy scheduling plans for water conservancy projects; Performing a water conservancy preview on all the water conservancy scheduling plans to obtain preview data for each of the water conservancy scheduling plans; According to all the preview data, all the water conservancy scheduling schemes are divided into order to obtain a scheme order set, wherein the scheme order set includes a plurality of water conservancy orders, and each water conservancy order corresponds to one of the scheme rankings of all the water conservancy scheduling schemes; A consistent scheduling decision is made on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project.

2. The method according to claim 1, characterized in that The method of obtaining several water conservancy scheduling plans for water conservancy projects includes: Obtaining a pre-trained language model and a water conservancy goal of the water conservancy project; Conducting consensus decision-making on the water conservancy goal through a number of different decision-makers, and obtaining consensus decision information corresponding to all the decision-makers; The consensus decision information is input into the pre-trained language model for solution analysis and extraction to obtain a plurality of water conservancy scheduling solutions.

3. The method according to claim 1, characterized in that According to all the preview data, all the water conservancy scheduling plans are divided into order to obtain a plan order set, including: Obtaining a number of decision bodies corresponding to all the water conservancy scheduling plans; Based on all the preview data, all the decision-makers are evaluated for indicators to obtain a decision matrix for each decision-maker, wherein the decision matrix includes a plurality of matrix elements, each of which is used to indicate an indicator evaluation value of the decision-maker for the corresponding water conservancy scheduling plan; According to all the decision matrices, all the water conservancy scheduling plans are sorted to obtain the plan order set.

4. The method according to claim 3, characterized in that The step of performing an index evaluation on all the decision bodies based on all the preview data to obtain a decision matrix for each decision body includes: Obtaining a pre-trained language model and an indicator prompt word template, as well as attribute information of the decision body; Constructing an indicator prompt word according to the indicator prompt word template and the attribute information; Inputting the indicator prompt into the pre-trained language model to generate indicators, and obtaining an evaluation indicator table for the decision body; According to the evaluation index table, the preview data is subjected to index analysis to obtain the decision matrix.

5. The method according to claim 3, characterized in that The method of sorting all the water conservancy scheduling schemes according to all the decision matrices to obtain the scheme order set includes: Performing matrix normalization on the decision matrix to obtain a normalized matrix; According to all the water conservancy scheduling plans, performing distance analysis on the normalized matrix to obtain a plan distance of each of the water conservancy scheduling plans; According to the distances of all the schemes, all the water conservancy scheduling schemes are sorted by distance to obtain the water conservancy order.

6. The method according to claim 5, characterized in that The solution distance includes a positive solution distance and a negative solution distance. The distance analysis is performed on the normalized matrix based on all the water conservancy scheduling solutions to obtain the solution distance of each water conservancy scheduling solution, including: Performing weighted normalization on the normalized matrix to obtain a weighted normalized matrix; According to the water conservancy scheduling plan, an ideal solution calculation is performed on the weighted normalized matrix to obtain a positive ideal solution and a negative ideal solution; According to the positive ideal solution and the negative ideal solution, distance calculation is performed on the weighted normalization matrix to obtain the positive solution distance and the negative solution distance.

7. The method according to claim 1, characterized in that The step of performing consistent scheduling decisions on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project includes: Obtaining a plurality of decision bodies corresponding to the scheme order set; Performing a local order expectation analysis on each water conservancy order according to all the decision bodies to obtain a plurality of first expected values, wherein the first expected values are used to represent the expected value of a single decision body for the corresponding water conservancy order; Performing a global order expectation analysis on all the water conservancy orders according to all the decision bodies to obtain a plurality of second expected values, wherein the second expected values are used to represent the expected values of all the decision bodies for the corresponding water conservancy orders; Based on all the first expected values and all the second expected values, all the water conservancy orders are screened for consistency decisions to obtain water conservancy scheduling information of the water conservancy project.

8. A decision-making and dispatching system for water conservancy projects, characterized in that: include: The first processing unit is used to obtain several water conservancy scheduling plans for the water conservancy project; A second processing unit is configured to perform a water conservancy preview on all the water conservancy scheduling plans to obtain preview data for each of the water conservancy scheduling plans; a third processing unit, configured to rank all the water conservancy scheduling schemes according to all the preview data to obtain a scheme order set, wherein the scheme order set includes a plurality of water conservancy orders, each of which corresponds to one of the scheme rankings of all the water conservancy scheduling schemes; The fourth processing unit is used to make a consistent scheduling decision on all water conservancy orders in the scheme sequence set to obtain water conservancy scheduling information of the water conservancy project.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

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