Efficiency evaluation method and device for regional water-energy-food link system

Abstract

The invention discloses an efficiency evaluation method and device for a regional water-energy-food link system, and the method comprises the steps: building an efficiency evaluation index system of the water-energy-food link system through combining the incidence relation among three subsystems; the three subsystems are a water resource subsystem, an energy subsystem and a food subsystem; external input data and external output data of the subsystems and internal input data and internal output data between the subsystems are obtained, and input data are obtained; establishing a fuzzy relation type network data packet analysis model according to the efficiency evaluation system to obtain a first model; the first model is constrained by external input-output relationships of the subsystems and internal association relationships among the subsystems; and inputting the input data into the first model for solving to obtain an efficiency evaluation result of the regional water-energy-food link system. The method can improve the accuracy and authenticity of efficiency evaluation of the link system, and can be widely applied to the technical field of computers.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an efficiency evaluation method and device for a regional water-energy-food linkage system. Background Art

[0002] Water resources, energy and food are key basic resources for economic development and people's livelihood. There is a complex interaction between the three resources. Energy and food production depend on a reliable and stable supply of water resources. The development, use and recycling of water resources are inseparable from the support of energy. Food production and food processing rely on energy such as pesticides, fertilizers and electricity. The interdependence between resources is close.

[0003] Data envelopment analysis (DEA) is a method based on mathematical programming models to evaluate the relative efficiency of production possibilities consisting of decision-making units. This method has achieved rich research results in water resource utilization, agricultural ecological efficiency and energy utilization evaluation. With the rise of research on the water-energy-food (WEF) linkage system, DEA series methods have gradually gained attention in the research on the efficiency evaluation of the WEF linkage system. Using traditional DEA methods, the WEF system is often generalized as a black box, considering only the input and output outside the system, that is, ignoring the internal subsystems and their relationships. In addition, most traditional DEA models are based on radial assumptions, that is, assuming that the increase and decrease of input and output indicators are in the same proportion, but this is quite different from the actual scenario where different parameters have different regulation proportions.

[0004] The network DEA method can open the black box and deconstruct the "black box" system according to the production process, so as to more accurately describe the internal structure of the system and its connections, and has received attention in the WEF efficiency evaluation. The SBM model can solve the limitations of the traditional DEA model and allow any indicators to change according to their respective proportions. However, the network SBM-DEA method still has the following two problems to be solved. First, although previous studies have introduced network structures into WEF efficiency research, the subsystems are still independent of each other. These studies assume that the intermediate variables produced by a subsystem are completely equal to the inputs of another subsystem. However, since the water, energy and food subsystems are all operated independently, it is difficult to achieve a situation where the inputs and outputs between subsystems are completely consistent. It is often required that the supply of a subsystem is greater than or equal to the demand of another subsystem. But network DEA cannot handle such problems. Second, the network DEA model is difficult to handle uncertain information. Due to the randomness of natural factors and the ambiguity of subjective judgment, uncertainty is widespread and difficult to represent using deterministic data. Summary of the invention

[0005] In order to solve at least one of the above problems, the embodiments of the present application propose an efficiency evaluation method and device for a regional water-energy-food nexus system, aiming to achieve efficient and accurate efficiency estimation.

[0006] To achieve the above objectives, one aspect of an embodiment of the present application proposes an efficiency evaluation method for a regional water-energy-food linkage system, the method comprising:

[0007] Combined with the correlation between the three subsystems, an efficiency evaluation index system of the water-energy-food linkage system is established; wherein the three subsystems are the water resources subsystem, the energy subsystem and the food subsystem;

[0008] Obtaining external input data and external output data of each of the subsystems in the region, as well as internal input data and internal output data between the subsystems, to obtain input data; wherein the data corresponding to the evaluation index with uncertainty is represented by a fuzzy value;

[0009] A fuzzy relational network data packet analysis model is established according to the efficiency evaluation system to obtain a first model; wherein the first model is constrained by the external input-output relationship of each of the subsystems and the internal association relationship between the subsystems;

[0010] The input data is input into the first model for solving, and the regional water-energy-food linkage system efficiency evaluation result is obtained.

[0011] In some embodiments, the method of establishing an efficiency evaluation index system for the water-energy-food linkage system by combining the association relationship among the three subsystems includes the following steps:

[0012] Constructing external input indicators; wherein the external input indicators include capital input indicators and labor input indicators of each subsystem; the external input indicators also include water resource usage indicators of the water resource subsystem, total energy consumption indicators of the energy subsystem, and irrigation area indicators of the food subsystem;

[0013] Constructing external output indicators; wherein the external output indicators include the secondary industry output value indicators and the tertiary industry output value indicators related to water in the water resources subsystem; the external output indicators also include the secondary industry output value indicators and the tertiary industry output value indicators related to energy in the energy subsystem; the external output indicators also include the primary industry total output value indicators in the food subsystem;

[0014] Constructing internal input-output indicators; wherein, the internal input-output indicators include energy water use indicators and agricultural water use indicators provided by the water resources system to the energy subsystem and the food subsystem; the internal input-output indicators also include indicators for water resources production energy and agricultural production energy provided by the energy subsystem to the water resources subsystem and the food subsystem.

[0015] An efficiency evaluation index system for the water-energy-food linkage system is established based on the external input index, the external output index and the internal input-output index.

[0016] In some embodiments, the acquiring of external input data and external output data of each of the subsystems in the region, and internal input data and internal output data between the subsystems to obtain input data includes:

[0017] Obtaining capital input data and labor data of each subsystem, water resource usage data of the water resource subsystem, total energy consumption data of the energy subsystem, and irrigation area data of the food subsystem to obtain external input data;

[0018] Obtain the total output value of the primary industry, the output value of the secondary and tertiary industries related to water, and the output value of the secondary and tertiary industries related to energy to obtain external output data;

[0019] Obtain the energy water consumption provided by the water resource subsystem to the energy subsystem, the agricultural water consumption provided by the water resource system to the food subsystem, the energy for water resource production provided by the energy subsystem to the water resource subsystem, and the agricultural production energy provided by the energy subsystem to the food subsystem to obtain internal input-output data;

[0020] The external input data, the external output data and the internal input-output data are used as input data.

[0021] In some embodiments, the step of establishing a fuzzy relational network data packet analysis model according to the efficiency evaluation system to obtain a first model includes the following steps:

[0022] Determine the objective function according to the ratio of the ineffectiveness of external inputs and the ineffectiveness of external outputs of the water resources subsystem, the energy subsystem and the food subsystem;

[0023] Determining constraint conditions according to the external input-output relationship of each of the subsystems and the internal association relationship of the subsystems;

[0024] According to the objective function, the constraint conditions and the association relationship, a fuzzy relational network data packet analysis model is established to obtain a first model.

[0025] In some embodiments, inputting the input data into the first model for solving to obtain the efficiency evaluation result of the regional water-energy-food nexus system comprises the following steps:

[0026] Using Charnes-Cooper transformation, the first model is transformed into a model with linearized objective function to obtain a second model;

[0027] Based on fuzzy theory, convert the fuzzy value in the input data into deterministic data to obtain intermediate data;

[0028] According to the upper limit condition and the lower limit condition of the water-energy-food nexus system, the second model is converted into an upper limit sub-model and a lower limit sub-model; wherein the upper limit condition is the minimum input and the maximum output; and the lower limit condition is the maximum input and the minimum output;

[0029] The optimal solutions of the upper limit sub-model and the lower limit sub-model are solved according to the intermediate data to obtain the efficiency evaluation results of the regional water-energy-food nexus system.

[0030] In some embodiments, the objective function is expressed as:

[0031]

[0032] in, Indicates DMU o Fuzzy efficiency, DMU is the regional water-energy-food linkage system; I k Indicates that subsystem k has I k External input data; R k Indicates that subsystem k has R k External output data; is the fuzzy value of the external input data of subsystem k; is the fuzzy value of the external output data of subsystem k; represents the slack variable of the external input data i of subsystem k; Remaining variables representing the external output data r of subsystem k; among the variables, when k=1, it represents the variable of the water resources subsystem; when k=2, it represents the variable of the energy subsystem; when k=3, it represents the variable of the food subsystem.

[0033] To achieve the above purpose, another aspect of the embodiment of the present application provides an efficiency evaluation device for a regional water-energy-food linkage system, the device comprising:

[0034] The first module is used to establish an efficiency evaluation index system for the water-energy-food linkage system by combining the correlation between the three subsystems; wherein the three subsystems are the water resources subsystem, the energy subsystem and the food subsystem;

[0035] The second module is used to obtain the external input data and external output data of each of the subsystems in the region, as well as the internal input data and internal output data between the subsystems, to obtain input data; wherein the data corresponding to the evaluation index with uncertainty is represented by a fuzzy value;

[0036] The third module is used to establish a fuzzy relational network data packet analysis model according to the efficiency evaluation system to obtain a first model; wherein the first model is constrained by the external input-output relationship of each of the subsystems and the internal association relationship between the subsystems;

[0037] The fourth module is used to input the input data into the first model for solving, so as to obtain the efficiency evaluation result of the regional water-energy-food linkage system.

[0038] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above-mentioned method when executing the computer program.

[0039] To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0040] The embodiments of the present application include at least the following beneficial effects: The embodiments of the present application combine the correlation between the subsystems in the regional water-energy-food nexus system, establish a network model of fuzzy relations, and can quantify the correlation between the subsystems in the regional water-energy-food nexus system, thereby improving the ability to handle the correlation between the subsystems, thereby making a true and accurate assessment of the efficiency of the nexus system. The embodiments of the present application can also handle the uncertainty represented as a fuzzy set, thereby improving the authenticity and accuracy of the system efficiency assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide further understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0042] Figure 1 It is a flow chart of an efficiency evaluation method of a regional water-energy-food linkage system provided in an embodiment of the present application;

[0043] Figure 2 It is a schematic diagram of the regional water-energy-food linkage system network relationship and the efficiency measurement index system provided by the embodiment of the present application;

[0044] Figure 3 It is a module schematic diagram of an efficiency evaluation device for a regional water-energy-food linkage system provided in an embodiment of the present application;

[0045] Figure 4 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0047] Although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first / S100", "second / S200", etc. in the specification, claims and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0048] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0049] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0050] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0052] Before describing the embodiments of the present application in detail, some nouns and terms involved in the embodiments of the present application are first described. The nouns and terms that may be involved in the embodiments of the present application are subject to the following explanations.

[0053] (1) WEF (Water-Energy-Food), the water-energy-food link.

[0054] (2) DEA (data envelopment analysis): The evaluation object is generally called decision-making unit, abbreviated as DMU.

[0055] (3) The DEA model based on slack-base measure (SBM), generally referred to as SBM-DEA model or SBM model, is a non-radial DEA model. In the radial DEA model, the input and output indicators are set to increase or decrease at the same rate at the same time. However, in the non-radial model, the input and output indicators increase or decrease at a certain rate, without having to follow the setting of the same rate and direction.

[0056] (4) Relational network DEA (Relational network data envelopment analysis): relational network data envelopment analysis model.

[0057] (5) Fuzzy DEA (fuzzy data envelopment analysis): fuzzy data envelopment analysis model.

[0058] In the related technology, the network SBM-DEA method still has the following two problems to be solved. First, although previous studies have introduced network structure into WEF efficiency research, the subsystems are still independent of each other. These studies assume that the intermediate variables produced by a subsystem are completely equal to the input of another subsystem. However, since the water, energy and food subsystems are all operated independently, it is difficult to achieve a situation where the input and output between subsystems are completely consistent. It is often required that the supply of a subsystem is greater than or equal to the demand of another subsystem. But network DEA cannot handle such problems. Another challenge is that the network DEA model has difficulty in handling uncertain information. Due to the randomness of natural factors and the ambiguity of subjective judgment, uncertainty is widespread and difficult to represent using deterministic data.

[0059] In view of this, the present application provides an efficiency evaluation method and device for a regional water-energy-food linkage system. The scheme takes the linkage relationship into consideration and establishes a fuzzy relational network SBM-DEA model for WEF efficiency measurement research from the perspective of linkage relationship. The established method can quantify the association relationship between subsystems, and the intermediate products supplied by the subsystem are constrained to meet (greater than or equal to) the needs of another subsystem. Moreover, the method can also process uncertainty information represented as fuzzy numbers.

[0060] The efficiency evaluation method of a regional water-energy-food linkage system provided in an embodiment of the present application relates to the field of computer technology. The efficiency evaluation method of a regional water-energy-food linkage system provided in an embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or it can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms and other basic cloud computing services. The server can also be a node server in a blockchain network; the software can be an application that implements an efficiency evaluation method for a regional water-energy-food linkage system, etc., but is not limited to the above forms.

[0061] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0062] Figure 1 is an optional flow chart of a method for evaluating the efficiency of a regional water-energy-food linkage system provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S100 to S400.

[0063] Step S100, combining the association relationship between the three subsystems, establishing an efficiency evaluation index system for the water-energy-food linkage system; wherein the three subsystems are the water resources subsystem, the energy subsystem and the food subsystem.

[0064] Step S200, obtaining external input data and external output data of each of the subsystems in the region, as well as internal input data and internal output data between the subsystems, to obtain input data; wherein data corresponding to evaluation indicators with uncertainty are represented by fuzzy values.

[0065] Step S300, establishing a fuzzy relational network data packet analysis model according to the efficiency evaluation system to obtain a first model; wherein the first model is constrained by the external input-output relationship of each of the subsystems and the internal association relationship between the subsystems.

[0066] Step S400: input the input data into the first model for solving, and obtain the regional water-energy-food linkage system efficiency evaluation result.

[0067] Steps S100 to S400 shown in the embodiment of the present application, by establishing a fuzzy relational network DEA, improve the ability of the network DEA to handle the association relationships between various subsystems, and can also handle uncertainties represented as fuzzy sets, thereby improving the authenticity and accuracy of the system efficiency evaluation, which is beneficial to the evaluation of the regional water-energy-food nexus system.

[0068] In some embodiments, step S100 may include but is not limited to steps S110 to S140:

[0069] Step S110, constructing external input indicators; wherein the external input indicators include capital input indicators and labor input indicators of each subsystem; the external input indicators also include water resource usage indicators of the water resource subsystem, total energy consumption indicators of the energy subsystem, and irrigation area indicators of the food subsystem.

[0070] Step S120, constructing external output indicators; wherein the external output indicators include the secondary industry output value indicators and the tertiary industry output value indicators related to water in the water resources subsystem; the external output indicators also include the secondary industry output value indicators and the tertiary industry output value indicators related to energy in the energy subsystem; the external output indicators also include the primary industry total output value indicators in the food subsystem.

[0071] Step S130, constructing internal input-output indicators; wherein the internal input-output indicators include energy water use indicators and agricultural water use indicators provided by the water resources system to the energy subsystem and the food subsystem; the internal input-output indicators also include indicators for water resources production energy and agricultural production energy provided by the energy subsystem to the water resources subsystem and the food subsystem.

[0072] Step S140: Establishing an efficiency evaluation index system for the water-energy-food linkage system based on the external input index, the external output index and the internal input-output index.

[0073] In some embodiments, step S200 includes but is not limited to the following steps S210 to S240:

[0074] Step S210, obtaining the capital input data and labor data of each of the subsystems, the water resource usage data of the water resource subsystem, the total energy consumption data of the energy subsystem, and the irrigation area data of the food subsystem to obtain external input data.

[0075] Step S220, obtaining the total output value of the primary industry, the output value of the secondary industry and the output value of the tertiary industry related to water, and the output value of the secondary industry and the output value of the tertiary industry related to energy, to obtain external output data.

[0076] Step S230, obtain the energy water consumption provided by the water resources subsystem to the energy subsystem, the agricultural water consumption provided by the water resources system to the food subsystem, the energy for water resources production provided by the energy subsystem to the water resources subsystem, and the agricultural production energy provided by the energy subsystem to the food subsystem, to obtain internal input-output data.

[0077] Step S240: taking the external input data, the external output data and the internal input-output data as input data.

[0078] In some embodiments, step S300 includes but is not limited to the following steps S310 to S330:

[0079] Step S310, determining an objective function according to the ratio of the external input ineffectiveness to the external output ineffectiveness of the water resource subsystem, the energy subsystem and the food subsystem.

[0080] In step S310 of some embodiments, the objective function may be expressed as:

[0081]

[0082] in, Indicates DMU o Fuzzy efficiency, DMU is the regional water-energy-food linkage system; I k Indicates that subsystem k has I k External input data; R k Indicates that subsystem k has R k External output data; is the fuzzy value of the external input data of subsystem k; is the fuzzy value of the external output data of subsystem k; represents the slack variable of the external input data i of subsystem k; Remaining variables representing the external output data r of subsystem k; among the variables, when k=1, it represents the variable of the water resources subsystem; when k=2, it represents the variable of the energy subsystem; when k=3, it represents the variable of the food subsystem.

[0083] Step S320, determining constraint conditions according to the external input-output relationships of the subsystems and the internal association relationships of the subsystems.

[0084] Step S330, establishing a fuzzy relational network data packet analysis model according to the objective function, the constraint conditions and the association relationship to obtain a first model.

[0085] In some embodiments, step S400 includes but is not limited to the following steps S410 to S440:

[0086] Step S410: Using Charnes-Cooper transformation, the first model is converted into a model with linearized objective function to obtain a second model.

[0087] Step S420: based on fuzzy theory, convert the fuzzy value in the input data into deterministic data to obtain intermediate data.

[0088] In some embodiments, step S420 includes but is not limited to the following steps S421-S422:

[0089] Step S421, taking the external input data and the external output data in the input data as triangular fuzzy numbers, and determining the support set.

[0090] Step S422, using the α cut-off method, based on the upper and lower limits of the fuzzy value at the α level and according to the support set, determine the closed interval of the input data to obtain intermediate data.

[0091] Step S430, according to the upper limit condition and the lower limit condition of the water-energy-food linkage system, convert the second model into an upper limit sub-model and a lower limit sub-model; wherein the upper limit condition is the minimum input and the maximum output; and the lower limit condition is the maximum input and the minimum output.

[0092] Step S440, solving the optimal solutions of the upper limit sub-model and the lower limit sub-model according to the intermediate data to obtain the efficiency evaluation result of the regional water-energy-food nexus system.

[0093] The following is a detailed description and explanation of the solution of the embodiment of the present application in conjunction with a specific application example of a regional water-energy-food link system efficiency assessment scenario:

[0094] In an embodiment of the present application, a method for evaluating the efficiency of a regional water-energy-food linkage system is provided, which can be applied to evaluate the efficiency of a regional water-energy-food linkage system. In this embodiment, the method can be specifically performed according to the following steps 1 to 6:

[0095] Step 1: Identify the relationship between water resources, energy and food subsystems, and establish an evaluation index system for the efficiency of the water-energy-food nexus.

[0096] Furthermore, from the perspective of external input-output relationship, the external input of the water resources subsystem includes water-related capital, labor input and water resource usage, and the external output is the output value of the secondary and tertiary industries related to water. The external input of the energy subsystem is energy-related capital, labor input and total energy consumption, and the output is the output value of the secondary and tertiary industries related to energy. The external input of the food subsystem is food-related capital, labor input and irrigation area, and the output is the total output value of the primary industry, including the total output value of agriculture, forestry, fishery and animal husbandry and related service industries.

[0097] Four key indicators are selected for the input-output indicators within the link system. The water resources subsystem provides energy water and agricultural water to the energy subsystem and the food subsystem. Energy water can be represented by water data for thermal power generation. The energy subsystem provides water resources production energy and agricultural production energy to the water resources subsystem and the food subsystem. Water resources production energy includes the total energy consumption in the production and supply of tap water, sewage treatment and its recycling, seawater desalination, and other water treatment, utilization and distribution. Agricultural production energy is represented by rural electricity consumption. These data are obtained for subsequent processing.

[0098] Furthermore, the regional WEF tie system is considered as a decision-making unit, with n homogeneous decision-making units (DMUs) j , j = 1, 2, ..., n), where the internal structure of each decision-making unit is divided into three interrelated subsystems (k = 1 for water resources subsystem, k = 2 for energy subsystem, and k = 3 for food subsystem). Each subsystem k has i k =1,...,I k External Input For production k =1,...,R k External output The three subsystems of water, energy and food are connected through intermediate products, which are both the intermediate output of the previous subsystem and the intermediate input of the next subsystem. The water resources subsystem provides g=1,...,G intermediate products to the energy subsystem. Provide q=1,...,Q intermediate products to the food subsystem The energy subsystem provides p=1,...,P intermediate products to the water resources subsystem Provide l=1,...,L intermediate products to the food subsystem Based on this, the efficiency evaluation index system constructed in the embodiment of the present application can refer to Figure 2 .

[0099] Step 2: Obtain data on capital, labor, resource input, and economic output of water, energy, and food subsystems in each region and period, and use fuzzy numbers to represent evaluation indicators with uncertainty.

[0100] Specifically, the capital, labor, resource input and economic output data involved in the above evaluation indicators are obtained for subsequent data processing.

[0101] Step 3: Establish a fuzzy relational network data envelopment analysis model, including three related subsystems of water resources, energy and food.

[0102] Furthermore, the fuzzy relational network SBM model used to measure regional WEF efficiency specifically includes:

[0103] ①Objective function.

[0104] The objective function of this model is the ratio of external input ineffectiveness to external output ineffectiveness. The expression of the objective function is:

[0105]

[0106] in, Indicates DMU o The fuzzy efficiency, is the fuzzy input value, is the fuzzy output value, represents the slack variable of external input i of subsystem k, Remaining variable representing the external output r of subsystem k.

[0107] ②Constraints.

[0108] The constraints include the input-output relationship of water resources, energy and food subsystems, the correlation relationship between subsystems and non-negative constraints.

[0109] Specifically, the external input-output relationship of the water resources subsystem includes the external output constraints of the evaluated decision-making unit DMUo, the external input constraints and the assumption of variable returns to scale, which are expressed as follows (1b) to (1d):

[0110]

[0111] in, Indicates DMU j Strength coefficient of subsystem k.

[0112] The expression of the external input-output relationship of the energy subsystem is as follows (1e~1g):

[0113]

[0114] The expression of the external input-output relationship of the food subsystem is as follows (1h~1j):

[0115]

[0116] Furthermore, the relationship between subsystems includes the intermediate products provided by the water resources subsystem to the energy subsystem. To meet the needs of the energy system, the energy subsystem provides intermediate products to the water resources subsystem Meet the needs of the water resources subsystem, the intermediate products provided by the water resources subsystem to the food subsystem To meet the needs of the food subsystem, the energy subsystem provides intermediate products to the food subsystem Meeting the needs of the food subsystem.

[0117] Based on the above intermediate products, the relevant expressions that meet the requirements of each subsystem are as follows (1k)~(1n):

[0118]

[0119] The non-negative constraint expression of this model is as follows (1o):

[0120]

[0121] ③ Fuzzy efficiency of water, energy and food subsystems The calculation, specifically:

[0122] The fuzzy efficiency calculation expression of the water resources subsystem is as follows (2a):

[0123]

[0124] The fuzzy efficiency calculation expression of the energy subsystem is as follows (2b): (2b)

[0125]

[0126] The fuzzy efficiency calculation expression of the food subsystem is as follows (2c):

[0127]

[0128] The calculation formulas of the relevant parameters are as follows (2d) to (2k):

[0129]

[0130] in, Represents the intermediate output of the energy subsystem The amount of insufficient supply, Indicates the intermediate input that can be saved in the water resources subsystem The number of Represents the intermediate output of the water resources subsystem The amount of insufficient supply, Indicates the intermediate inputs that can be saved in the food subsystem The number of Represents the intermediate output of the energy subsystem The amount of insufficient supply, Indicates the intermediate inputs that can be saved in the food subsystem The number of Represents the intermediate output of the water resources subsystem The amount of insufficient supply, Indicates the intermediate inputs that can be saved in the food subsystem The number of

[0131] Step 4: Use Charnes-Cooper transformation to convert the fractional objective in the model into a linear form.

[0132] Furthermore, after constructing the above fuzzy relational network SBM model, in the solution process, the fractional objective is first transformed into a linear form using the Charnes-Cooper transformation. The specific transformation process is as follows: The following linearized model can be obtained, and the expression of the linearized model is:

[0133]

[0134] The constraints of the water resource subsystem of the linearized model are as follows (3b) to (3d):

[0135]

[0136] The constraints of the energy subsystem of the linearized model are as follows (3e) to (3g):

[0137]

[0138] The constraints of the food subsystem of the linearized model are as follows (3h) to (3j):

[0139]

[0140] The intermediate input-output constraints between subsystems are as follows (3k) to (3p):

[0141]

[0142] in, The optimal solution of the above model with a linear objective function is defined as The optimal solution of the original model (i.e. the fuzzy relational network SBM model for measuring regional WEF efficiency) can be obtained by the following calculation method:

[0143] Step 5: Use the α cut set to process the fuzzy numbers and decompose the model into two sub-models: upper limit and lower limit.

[0144] Furthermore, the external input indicators and external output indicators in the regional WEF linkage system are expressed as fuzzy numbers, which are converted into deterministic data using fuzzy theory. and The membership degree is and The triangular fuzzy numbers correspond to and As its support set, at any level of α, the following closed intervals (4a) to (4b) can be formed:

[0145]

[0146] in and are the lower and upper limits of the fuzzy number at level α, and are the lower and upper limits of the fuzzy number at level α respectively.

[0147] According to the concept of Pareto efficiency, the decision-making unit DMU o The upper and lower limits of can be obtained in the most favorable and most unfavorable scenarios, respectively. Therefore, the above linearized model can be converted into an upper limit sub-model and a lower limit sub-model for solution. The most favorable scenario corresponds to the conditions of minimum input and maximum output. The mathematical expression of the upper limit sub-model is shown in the following formula (5a):

[0148]

[0149] The constraints of the water resource subsystem of the upper limit submodel are as follows (5b) to (5d):

[0150]

[0151] The constraints of the energy subsystem of the upper limit submodel are as follows (5e) to (5g):

[0152]

[0153] The constraints of the food subsystem of the upper limit submodel are as follows (5h) to (5j):

[0154]

[0155] The intermediate input-output constraints between the subsystems of the upper limit submodel are as follows (5k) to (5p):

[0156]

[0157] The lower limit sub-model corresponds to the most unfavorable scenario, that is, the maximum input and minimum output conditions. The mathematical model expression of the lower limit sub-model of the embodiment of the present application is shown in the following formula (6a):

[0158]

[0159] The constraints of the water resource subsystem of the lower limit submodel include the following (6a) to (6d):

[0160]

[0161] The constraints of the energy subsystem of the lower limit submodel include the following (6e) to (6g):

[0162]

[0163] The constraints of the food subsystem of the lower limit submodel include the following (6h) to (6j):

[0164]

[0165] The intermediate input-output constraints between each subsystem of the lower limit submodel are as follows (6k) to (6p):

[0166]

[0167]

[0168] By solving the upper and lower limit sub-models, the optimal solution of the linear model can be obtained. Finally, the optimal solution of the fuzzy relational network SBM model for measuring regional WEF efficiency can be obtained through the following transformation:

[0169] In summary, the embodiments of the present application have at least the following beneficial effects:

[0170] The embodiment of the present application establishes a fuzzy relational network SBM-DEA model, which can quantify the association between subsystems in the regional water-energy-food linkage system. The intermediate products supplied by the subsystem are constrained to meet (greater than or equal to) the needs of another subsystem, thereby making a true and accurate evaluation of the efficiency of the linkage system. Moreover, this method can also process uncertainty information represented as fuzzy numbers, thereby improving the authenticity and accuracy of the system efficiency evaluation.

[0171] See also Figure 3 The embodiment of the present application also provides an efficiency evaluation device for a regional water-energy-food linkage system, which can implement the efficiency evaluation method for a regional water-energy-food linkage system, and the device includes:

[0172] The first module 101 is used to establish an efficiency evaluation index system of the water-energy-food linkage system by combining the association relationship between the three subsystems; wherein the three subsystems are the water resources subsystem, the energy subsystem and the food subsystem;

[0173] The second module 102 is used to obtain the external input data and external output data of each of the subsystems in the region, as well as the internal input data and internal output data between the subsystems, to obtain input data; wherein the data corresponding to the evaluation index with uncertainty is represented by a fuzzy value;

[0174] The third module 103 is used to establish a fuzzy relational network data packet analysis model according to the efficiency evaluation system to obtain a first model; wherein the first model is constrained by the external input-output relationship of each of the subsystems and the internal association relationship between the subsystems;

[0175] The fourth module 104 inputs the input data into the first model for solving, and obtains the regional water-energy-food linkage system efficiency evaluation results.

[0176] It can be understood that the contents of the above method embodiments are all 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.

[0177] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned method for evaluating the efficiency of a regional water-energy-food linkage system when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0178] It can be understood that the contents of the above method embodiments are all 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.

[0179] See also Figure 4 , Figure 4 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0180] The processor 201 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0181] The memory 202 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 202 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 202, and the processor 201 calls and executes the efficiency evaluation method of a regional water-energy-food nexus system in the embodiment of this application;

[0182] Input / output interface 203, used to implement information input and output;

[0183] The communication interface 204 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0184] Bus 205 , which transmits information between various components of the device (e.g., processor 201 , memory 202 , input / output interface 203 , and communication interface 204 );

[0185] The processor 201 , the memory 202 , the input / output interface 203 and the communication interface 204 are connected to each other in communication within the device via the bus 205 .

[0186] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned efficiency evaluation method of a regional water-energy-food nexus system.

[0187] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present 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.

[0188] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0189] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0190] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0191] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] Those skilled in the art will appreciate that all or some of the steps, devices, and functional modules / units in the above disclosed methods may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0193] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0194] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0195] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0196] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0197] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0198] If the integrated unit 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 all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0199] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for evaluating the efficiency of regional water-energy-food nexus systems, It is characterized in that The following steps are involved: Combined with the correlation between the three subsystems, an efficiency evaluation index system of the water-energy-food linkage system is established; wherein the three subsystems are the water resources subsystem, the energy subsystem and the food subsystem; Obtaining external input data and external output data of each of the subsystems in the region, as well as internal input data and internal output data between the subsystems, to obtain input data; wherein the data corresponding to the evaluation index with uncertainty is represented by a fuzzy value; A fuzzy relational network data packet analysis model is established according to the efficiency evaluation system to obtain a first model; wherein the first model is constrained by the external input-output relationship of each of the subsystems and the internal association relationship between the subsystems; The input data is input into the first model for solving, and the efficiency evaluation result of the regional water-energy-food nexus system is obtained.

2. The method according to claim 1, It is characterized in that The efficiency evaluation index system of the water-energy-food linkage system is established by combining the correlation between the three subsystems, including the following steps: Constructing external input indicators; wherein the external input indicators include capital input indicators and labor input indicators of each subsystem; the external input indicators also include water resource usage indicators of the water resource subsystem, total energy consumption indicators of the energy subsystem, and irrigation area indicators of the food subsystem; Constructing external output indicators; wherein the external output indicators include the secondary industry output value indicators and the tertiary industry output value indicators related to water in the water resources subsystem; the external output indicators also include the secondary industry output value indicators and the tertiary industry output value indicators related to energy in the energy subsystem; the external output indicators also include the primary industry total output value indicators in the food subsystem; Constructing internal input-output indicators; wherein, the internal input-output indicators include energy water use indicators and agricultural water use indicators provided by the water resources system to the energy subsystem and the food subsystem; the internal input-output indicators also include indicators for water resources production energy and agricultural production energy provided by the energy subsystem to the water resources subsystem and the food subsystem. An efficiency evaluation index system for the water-energy-food linkage system is established based on the external input index, the external output index and the internal input-output index.

3. The method according to claim 1, It is characterized in that The external input data and external output data of each of the subsystems in the acquisition area, as well as the internal input data and internal output data between the subsystems, are obtained to obtain input data, including: Obtaining capital input data and labor data of each subsystem, water resource usage data of the water resource subsystem, total energy consumption data of the energy subsystem, and irrigation area data of the food subsystem to obtain external input data; Obtain the total output value of the primary industry, the output value of the secondary and tertiary industries related to water, and the output value of the secondary and tertiary industries related to energy to obtain external output data; Obtain the energy water consumption provided by the water resource subsystem to the energy subsystem, the agricultural water consumption provided by the water resource system to the food subsystem, the energy for water resource production provided by the energy subsystem to the water resource subsystem, and the agricultural production energy provided by the energy subsystem to the food subsystem to obtain internal input-output data; The external input data, the external output data and the internal input-output data are used as input data.

4. The method according to claim 1, It is characterized in that The method of establishing a fuzzy relational network data packet analysis model according to the efficiency evaluation system to obtain a first model includes the following steps: Determine the objective function according to the ratio of the ineffectiveness of external inputs and the ineffectiveness of external outputs of the water resources subsystem, the energy subsystem and the food subsystem; Determining constraint conditions according to the external input-output relationship of each of the subsystems and the internal association relationship of the subsystems; According to the objective function, the constraint conditions and the association relationship, a fuzzy relational network data packet analysis model is established to obtain a first model.

5. The method according to claim 1, It is characterized in that The step of inputting the input data into the first model for solving the problem and obtaining the efficiency evaluation result of the regional water-energy-food linkage system comprises the following steps: Using Charnes-Cooper transformation, the first model is transformed into a model with linearized objective function to obtain a second model; Based on fuzzy theory, convert the fuzzy value in the input data into deterministic data to obtain intermediate data; According to the upper limit condition and the lower limit condition of the water-energy-food nexus system, the second model is converted into an upper limit sub-model and a lower limit sub-model; wherein the upper limit condition is the minimum input and the maximum output; and the lower limit condition is the maximum input and the minimum output; The optimal solutions of the upper limit sub-model and the lower limit sub-model are solved according to the intermediate data to obtain the efficiency evaluation results of the regional water-energy-food nexus system.

6. The method according to claim 4, It is characterized in that The expression of the objective function is: in, Indicates DMU o Fuzzy efficiency, DMU is the regional water-energy-food linkage system; I k Indicates that subsystem k has I k External input data; R k Indicates that subsystem k has R k External output data; is the fuzzy value of the external input data of subsystem k; is the fuzzy value of the external output data of subsystem k; represents the slack variable of the external input data i of subsystem k; Remaining variables representing the external output data r of subsystem k; among the variables, when k=1, it represents the variable of the water resources subsystem; when k=2, it represents the variable of the energy subsystem; when k=3, it represents the variable of the food subsystem.

7. The method according to claim 5, It is characterized in that The method of converting the fuzzy value in the input data into deterministic data based on fuzzy theory to obtain intermediate data includes the following steps: The external input data and the external output data in the input data are taken as triangular fuzzy numbers, and a support set is determined; The α cut-off method is adopted to determine the closed interval of the input data based on the upper and lower limits of the fuzzy value at the α level and the support set to obtain the intermediate data.

8. An efficiency evaluation device for a regional water-energy-food linkage system, It is characterized in that include: The first module is used to establish an efficiency evaluation index system for the water-energy-food linkage system by combining the correlation between the three subsystems; wherein the three subsystems are the water resources subsystem, the energy subsystem and the food subsystem; The second module is used to obtain the external input data and external output data of each of the subsystems in the region, as well as the internal input data and internal output data between the subsystems, to obtain input data; wherein the data corresponding to the evaluation index with uncertainty is represented by a fuzzy value; The third module is used to establish a fuzzy relational network data packet analysis model according to the efficiency evaluation system to obtain a first model; wherein the first model is constrained by the external input-output relationship of each of the subsystems and the internal association relationship between the subsystems; The fourth module is used to input the input data into the first model for solving, so as to obtain the efficiency evaluation result of the regional water-energy-food linkage system.

9. An electronic device, It is characterized in that including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method according to any one of claims 1 to 7.

10. A computer storage medium having a program executable by a processor stored therein, It is 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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