Agricultural irrigation scheme determination method and device, equipment, product and storage medium

Abstract

The invention provides an agricultural irrigation scheme determination method and device, equipment, a product and a storage medium, and relates to the technical field of agricultural production management. The method comprises the steps that a simulated irrigation scheme set is input into a prediction layer in an irrigation scheme prediction model, an irrigation scheme prediction result set output by the prediction layer is obtained, and irrigation scheme prediction results in the irrigation scheme prediction result set are in one-to-one correspondence with simulated irrigation schemes in the simulated irrigation scheme set; based on the key performance index set of each irrigation scheme prediction result in the irrigation scheme prediction result set, determining a comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set; and determining the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as an agricultural irrigation scheme. According to the invention, the defects of water resource waste and carbon emission increase caused by difficulty in accurately matching crop requirements due to an irrigation mode based on experience or a fixed mode in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural production management, and in particular to a method, device, equipment, product and storage medium for determining an agricultural irrigation plan. Background Art

[0002] Global water shortage and climate change problems are becoming increasingly serious. Agriculture, as a major water-consuming industry and source of greenhouse gas emissions, faces an urgent need to save water and reduce carbon emissions. However, traditional irrigation methods are usually based on experience or fixed patterns, which are difficult to accurately match crop needs, resulting in water waste and increased carbon emissions. For example, unreasonable irrigation methods can cause excessive soil wetting, promote the decomposition of organic matter and produce more greenhouse gases such as methane and nitrous oxide, further affecting the climate. Therefore, there is an urgent need for a method to determine agricultural irrigation plans to accurately match the actual needs of crops, optimize water utilization efficiency, and reduce greenhouse gas emissions, thereby achieving the goal of saving water and reducing carbon emissions. Summary of the invention

[0003] The present invention provides a method, device, equipment, product and storage medium for determining an agricultural irrigation plan, so as to solve the defects of the irrigation method in the prior art that it is based on experience or fixed patterns, is difficult to accurately match crop needs, and leads to waste of water resources and increased carbon emissions.

[0004] The present invention provides a method for determining an agricultural irrigation scheme, comprising: Inputting the simulated irrigation scheme set into the prediction layer in the irrigation scheme prediction model, obtaining the irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; Determine a comprehensive benefit score for each irrigation scheme prediction result in the irrigation scheme prediction result set based on a key performance indicator set for each irrigation scheme prediction result in the irrigation scheme prediction result set; The simulated irrigation scheme corresponding to the prediction result of the irrigation scheme with the highest comprehensive benefit score is determined as the agricultural irrigation scheme; The irrigation scheme prediction model is obtained by training based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0005] According to a method for determining an agricultural irrigation scheme provided by the present invention, before inputting the simulated irrigation scheme set into the prediction layer of the irrigation scheme prediction model, the method comprises: The preset agricultural configuration data set is input into the simulation layer in the irrigation plan prediction model to obtain a simulated irrigation plan set output by the simulation layer. The simulation layer is used to determine each preset agricultural configuration data in the preset agricultural configuration data set as a simulated irrigation plan to obtain a simulated irrigation plan set.

[0006] According to a method for determining an agricultural irrigation scheme provided by the present invention, the method of determining a comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on a key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set comprises: The key performance indicator set of the prediction results of each irrigation scheme is standardized to obtain a standardized performance indicator matrix; Based on the standardized performance indicator matrix, a covariance matrix is ​​constructed; Performing eigenvalue decomposition on the covariance matrix to obtain an eigenvalue set and an eigenvector set; each eigenvalue in the eigenvalue set corresponds to each eigenvector in the eigenvector set in one-to-one correspondence; Determining a principal component set from the eigenvector set based on the sorting results of the eigenvalues ​​in the eigenvalue set; Based on the standardized performance indicator matrix and the principal component set, determining the score of each irrigation scheme prediction result on each principal component in the principal component set; Based on the score of each irrigation scheme prediction result on each principal component in the principal component set and the weight of each principal component in the principal component set, the comprehensive benefit score of each irrigation scheme prediction result is determined.

[0007] According to a method for determining an agricultural irrigation scheme provided by the present invention, a key performance indicator set of a prediction result of each irrigation scheme is standardized based on the following standardized formula: ; in, Indicates i The irrigation scheme prediction results are in j The original values ​​of the key performance indicators, The first j The mean of the key performance indicators, The first j The standard deviation of the key performance indicators, Indicates the normalized value.

[0008] According to a method for determining an agricultural irrigation scheme provided by the present invention, a covariance matrix C is constructed based on the following formula: ; in, represents the transpose of the standardized performance indicator matrix, Z represents the standardized performance indicator matrix, and n represents the number of irrigation scheme prediction results.

[0009] According to a method for determining an agricultural irrigation scheme provided by the present invention, the weight of each principal component in the principal component set is obtained based on the normalization of the eigenvalue corresponding to each principal component in the principal component set.

[0010] The present invention also provides an agricultural irrigation scheme determination device, comprising: A prediction module, which is used to input the simulated irrigation scheme set into the prediction layer in the irrigation scheme prediction model, and obtain the irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; A comprehensive benefit score determination module, which is used to determine the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on a key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set; An agricultural irrigation scheme determination module is used to determine the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme; The irrigation scheme prediction model is obtained by training based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0011] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for determining an agricultural irrigation scheme as described above is implemented.

[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for determining an agricultural irrigation scheme as described in any one of the above is implemented.

[0013] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for determining an agricultural irrigation scheme as described above is implemented.

[0014] The agricultural irrigation scheme determination method, device, equipment, product and storage medium provided by the present invention input a simulated irrigation scheme set into a prediction layer in an irrigation scheme prediction model to obtain an irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds one-to-one to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; based on the key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set, a comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set is determined; and the irrigation scheme prediction result with the highest comprehensive benefit score is selected. The corresponding simulated irrigation scheme is determined to be an agricultural irrigation scheme; wherein the irrigation scheme prediction model is obtained by training based on the sample irrigation scheme and the irrigation scheme prediction result labels corresponding to the sample irrigation scheme; the present invention generates irrigation scheme prediction results corresponding to the simulated irrigation schemes one by one by inputting a variety of possible simulated irrigation schemes into the irrigation scheme prediction model, and then comprehensively evaluates the key performance indicator set of each irrigation scheme prediction result to ensure that the selected agricultural irrigation scheme achieves the best balance in resource utilization efficiency and environmental impact, thereby avoiding over-irrigation or under-irrigation, optimizing the utilization efficiency of water resources, and thus providing important support for achieving the goals of water conservation and carbon reduction in agriculture. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a flow chart of the method for determining an agricultural irrigation scheme provided by the present invention.

[0017] Figure 2 It is a structural schematic diagram of the agricultural irrigation scheme determination device provided by the present invention.

[0018] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Through long-term research, the applicant of this patent has found that with the increasing severity of global water shortage and climate change problems, agriculture, as a major water-consuming industry and source of greenhouse gas emissions, has an increasingly urgent need to save water and reduce carbon emissions. However, existing irrigation methods mostly rely on experience or fixed patterns, which are difficult to accurately match crop growth needs, resulting in water waste and increased greenhouse gas emissions. In particular, unreasonable irrigation methods can cause excessive soil wetting, which in turn promotes the emission of greenhouse gases such as methane and nitrous oxide, and has an adverse impact on the ecosystem and climate.

[0021] Further research found that although some technologies have attempted to optimize irrigation strategies through model simulation or data-driven methods, there are still many shortcomings. Most of these technologies lack intuitive automated decision support, which means that agricultural producers still need to rely on experience and judgment when choosing irrigation plans, making it difficult to quickly determine the optimal plan.

[0022] In view of the above problems, the present invention proposes the following embodiments.

[0023] Figure 1 FIG. 1 is a flow chart of the method for determining an agricultural irrigation scheme provided by the present invention. Figure 1 As shown, the method includes the following: Step 110, input the simulated irrigation plan set into the prediction layer in the irrigation plan prediction model to obtain the irrigation plan prediction result set output by the prediction layer, wherein each irrigation plan prediction result in the irrigation plan prediction result set corresponds one-to-one to each simulated irrigation plan in the simulated irrigation plan set; each irrigation plan prediction result includes a key performance indicator set.

[0024] The irrigation scheme prediction model is obtained by training based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0025] It should be noted that the simulated irrigation scheme usually includes multiple parameters, such as irrigation amount, irrigation frequency, irrigation duration and environmental variables, etc. The irrigation scheme prediction model is pre-trained with sample irrigation schemes and the irrigation scheme prediction result labels corresponding to the sample irrigation schemes, and is used to simulate the actual performance of different irrigation schemes, and can identify the relationship between the simulated irrigation schemes and the key performance indicators in the irrigation scheme prediction results.

[0026] For example, the key performance indicator set may include, but is not limited to, crop yield, water resource utilization efficiency, and environmental friendliness, wherein environmental friendliness may be evaluated by Global Warming Potential (GWP) and Greenhouse Gas Intensity (GHGI).

[0027] For the specific method of generating the simulated irrigation plan set, please refer to the following embodiment, which will not be elaborated here.

[0028] Step 120: determining a comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on a key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set.

[0029] For example, comprehensive evaluation methods such as principal component analysis (PCA), technique for order preference by similarity to ideal solution (TOPSIS), and grey correlation can be used to quantitatively evaluate the key performance indicator set of each irrigation scheme prediction result to determine the comprehensive benefit score of each irrigation scheme prediction result.

[0030] The specific operation of quantitatively evaluating the key performance indicator set of the prediction result of each irrigation scheme can be referred to the following embodiment, which will not be described in detail here.

[0031] Step 130, determining the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme.

[0032] Here, the comprehensive benefit score reflects the comprehensive performance of the irrigation scheme on multiple key performance indicators. The higher the score, the greater the overall advantage of the scheme in terms of water saving, carbon reduction and crop yield.

[0033] Determining the simulated irrigation scheme with the highest comprehensive benefit score as the agricultural irrigation scheme ensures that the selected scheme is based on the results of scientific calculation and comprehensive evaluation.

[0034] The agricultural irrigation scheme determination method provided by the embodiment of the present invention generates irrigation scheme prediction results that correspond to the simulated irrigation schemes one by one by inputting multiple possible simulated irrigation schemes into the irrigation scheme prediction model, and then comprehensively evaluates the key performance indicator set of each irrigation scheme prediction result to ensure that the selected agricultural irrigation scheme achieves the best balance between resource utilization efficiency and environmental impact, thereby avoiding over-irrigation or under-irrigation, optimizing the utilization efficiency of water resources, and thus providing important support for achieving the goals of water conservation and carbon reduction in agriculture.

[0035] Based on any of the above embodiments, in the method, before inputting the simulated irrigation scheme set into the prediction layer in the irrigation scheme prediction model, the method includes: The preset agricultural configuration data set is input into the simulation layer in the irrigation plan prediction model to obtain a simulated irrigation plan set output by the simulation layer. The simulation layer is used to determine each preset agricultural configuration data in the preset agricultural configuration data set as a simulated irrigation plan to obtain a simulated irrigation plan set.

[0036] Here, each preset agricultural configuration data set includes multiple configuration parameters, such as crop type, soil type, climate conditions and other parameters. Since the values ​​of the parameters can be set to different values, multiple preset agricultural configuration data can be determined to obtain a preset agricultural configuration data set.

[0037] Here, the simulation layer is a functional module in the irrigation scheme prediction model, which is used to simulate a simulated irrigation scheme that meets actual production needs based on the input preset agricultural configuration data. The preset agricultural configuration data corresponds to the simulated irrigation scheme one by one.

[0038] For example, the irrigation scheme prediction model may be trained based on an Agricultural Production Systems Simulator (APSIM) model.

[0039] The agricultural irrigation scheme determination method provided by the embodiment of the present invention generates a set of simulated irrigation schemes that match actual agricultural production conditions by inputting a preset agricultural configuration data set into the simulation layer of the irrigation scheme prediction model. This method uses the simulation layer to map each preset agricultural configuration data into a specific simulated irrigation scheme, which can fully consider the differences in different environments, soils, climates, and crop growth characteristics, and ensure that the generated simulated irrigation scheme is more targeted and scientific. Through this step, the accuracy and reliability of subsequent irrigation scheme predictions are significantly improved, while providing diversified data support for comprehensive benefit analysis, ultimately helping to identify more efficient and sustainable agricultural irrigation strategies.

[0040] Based on any of the above embodiments, in the method, determining the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on the key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set includes: The key performance indicator set of the prediction results of each irrigation scheme is standardized to obtain a standardized performance indicator matrix; Based on the standardized performance indicator matrix, a covariance matrix is ​​constructed; Performing eigenvalue decomposition on the covariance matrix to obtain an eigenvalue set and an eigenvector set; each eigenvalue in the eigenvalue set corresponds to each eigenvector in the eigenvector set in one-to-one correspondence; Determining a principal component set from the eigenvector set based on the sorting results of the eigenvalues ​​in the eigenvalue set; Based on the standardized performance indicator matrix and the principal component set, determining the score of each irrigation scheme prediction result on each principal component in the principal component set; Based on the score of each irrigation scheme prediction result on each principal component in the principal component set and the weight of each principal component in the principal component set, the comprehensive benefit score of each irrigation scheme prediction result is determined.

[0041] It should be noted that the key performance indicator set may have different dimensions, so it is necessary to convert it into a dimensionless form through standardization to obtain a standardized performance indicator matrix for unified comparison. The covariance matrix reflects the linear correlation between the indicators, reveals the redundant information between the indicators, and provides basic data for subsequent eigenvalue decomposition and principal component analysis.

[0042] Furthermore, by sorting the eigenvalues, the first few principal components with higher cumulative contribution rates are selected as the principal component set to ensure that most of the original information of the data is retained, so as to achieve dimensionality reduction processing, reduce computational complexity, and retain the main features of the data.

[0043] Furthermore, the weighted comprehensive benefit score is calculated according to the principal component scores and the weights of the principal components to achieve a comprehensive evaluation of different irrigation schemes and provide a basis for the subsequent selection of the optimal scheme.

[0044] Here, the eigenvalue represents the importance of the principal component. The eigenvector represents the direction of the principal component and is the key to dimensionality reduction.

[0045] Exemplarily, the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set is determined based on the principal component analysis method. In addition, the relative closeness of each irrigation scheme prediction result in the irrigation scheme prediction result set can be evaluated by the ideal solution approximation method, and the one with the largest relative closeness is selected as the agricultural irrigation scheme. The relative closeness here is equivalent to the comprehensive benefit score; the correlation of each irrigation scheme prediction result in the irrigation scheme prediction result set can also be evaluated by the gray correlation method, and the irrigation scheme prediction result with the strongest correlation is selected as the agricultural irrigation scheme. In addition, the principal component analysis method, the ideal solution approximation method and the gray correlation method can be used simultaneously to simultaneously evaluate the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set, thereby determining the optimal agricultural irrigation scheme.

[0046] For example, if the relative closeness of the prediction results of each irrigation scheme in the irrigation scheme prediction result set is evaluated by the ideal solution approximation method, it is necessary to first establish a decision matrix, and the scores of the prediction results of each irrigation scheme on different indicators form a decision matrix, which is recorded as X = [xij ], where x ij It represents the value of the prediction result of the ith irrigation scheme on the jth indicator. Furthermore, in order to eliminate the influence of different indicator dimensions, the decision matrix needs to be normalized, which can be normalized based on the following formula: ; Among them, r ij is the normalized value. Furthermore, different weights w are assigned according to the importance of each indicator. j , and then calculate the weighted normalized decision matrix, which can be weighted based on the following formula: ; Among them, w j is the weight of the jth indicator.

[0047] Further, determine the ideal solution and negative ideal solution, the ideal solution A + and negative ideal solution A - They are: ； ； Among them, J benefit and J cost They represent the collection of benefit-type indicators and cost-type indicators respectively.

[0048] Furthermore, the Euclidean distance is used to calculate the distance between the predicted result of each irrigation scheme and the ideal solution and the negative ideal solution, as described in the following formula: ; ; in, is the distance between the predicted result of the ith irrigation scheme and the ideal solution, is the distance between the predicted result of the ith irrigation scheme and the negative ideal solution. Furthermore, according to the distance between the predicted result of the irrigation scheme and the ideal solution and the negative ideal solution, the relative closeness of the predicted result of each irrigation scheme is calculated. , the formula is: ; Relative closeness The closer it is to 1, the better the irrigation scheme prediction result is. Finally, according to the relative closeness of the prediction results of each irrigation scheme Sort them and select the simulated irrigation plan corresponding to the irrigation plan prediction result with the largest relative closeness as the agricultural irrigation plan.

[0049] For example, if the grey correlation method is used to evaluate the correlation of each irrigation scheme prediction result in the irrigation scheme prediction result set, the objects and indicators to be analyzed are first selected and combined into a data sequence. Assume that there are m irrigation scheme prediction results and n key performance indicators, forming a decision matrix ,in The value of the predicted result of the i-th irrigation scheme on the j-th key performance indicator. Further, the reference sequence is determined, which is usually composed of the optimal value or target value of each key performance indicator. It is denoted as ,in is the value of the reference sequence at the jth key performance indicator. Since the dimensions of each indicator are different, in order to eliminate the impact of the dimension, the original data needs to be dimensionless. The commonly used method is shown in the following formula: Extreme value normalization: ; Standardization: ; in, is the mean value of the jth key performance indicator, is the standard deviation of the jth key performance indicator. Furthermore, based on the dimensionless processed data, the correlation coefficient between the prediction results of each irrigation scheme and the reference sequence on each key performance indicator is calculated. The calculation formula of the correlation coefficient is: ; in, is the absolute value of the difference between the prediction result of the i-th irrigation scheme and the reference sequence in the j-th key performance indicator; and are the minimum and maximum absolute values ​​of all differences, respectively; is the resolution coefficient, which is generally between 0 and 1. .

[0050] Furthermore, the correlation coefficient of each scheme is weighted according to the importance of the key performance indicators to obtain the grey correlation degree between the prediction results of each irrigation scheme and the reference sequence. The formula is: ; in, is the weight of the jth key performance indicator. The prediction results of each irrigation scheme are sorted according to the size of . The larger the grey correlation, the stronger the correlation between the prediction result of the irrigation scheme and the reference sequence, and the better the prediction result of the irrigation scheme. The simulated irrigation scheme corresponding to the prediction result of the irrigation scheme with the strongest correlation is selected as the agricultural irrigation scheme.

[0051] The method for determining an agricultural irrigation scheme provided by the embodiment of the present invention standardizes the key performance indicator set of the irrigation scheme prediction results, eliminates the dimensional differences between different indicators, and makes them comparable; uses the covariance matrix to reveal the correlation between the indicators, extracts the principal components through eigenvalue decomposition, reduces the data dimension, reduces redundant information, and ensures that most of the key information is retained; calculates the comprehensive benefit score through the principal component score, reasonably integrates the importance and weight of each indicator, and ensures the scientificity and comprehensiveness of the evaluation. This process significantly improves the efficiency and accuracy of irrigation scheme evaluation, provides a reliable basis for selecting the optimal irrigation scheme, helps to accurately match crop needs, optimize resource utilization, and ultimately achieve the goal of water saving and emission reduction.

[0052] Based on any of the above embodiments, in the method, the key performance indicator set of each irrigation scheme prediction result is standardized based on the following standardized formula: ; in, Indicates i The irrigation scheme prediction results are in j The original values ​​of the key performance indicators, The first j The mean of the key performance indicators, The first j The standard deviation of the key performance indicators, Indicates the normalized value.

[0053] The agricultural irrigation scheme determination method provided in the embodiment of the present invention converts the indicator values ​​in the prediction results of different irrigation schemes into dimensionless standardized values ​​by applying a standardized formula to a set of key performance indicators, thereby eliminating the influence caused by dimensional differences and orders of magnitude, and making the indicators comparable.

[0054] Based on any of the above embodiments, in this method, the covariance matrix C is constructed based on the following formula: ; in, represents the transpose of the standardized performance indicator matrix, Z represents the standardized performance indicator matrix, and n represents the number of irrigation scheme prediction results.

[0055] The agricultural irrigation scheme determination method provided by the embodiment of the present invention can quantify the correlation between different key performance indicators by constructing a covariance matrix, providing a data basis for subsequent eigenvalue decomposition and principal component extraction. This process comprehensively considers the data characteristics of all irrigation scheme prediction results, and can reveal the positive correlation, negative correlation or independence between indicators, thereby providing a scientific basis for extracting principal components in subsequent steps.

[0056] Based on any of the above embodiments, in the method, the weight of each principal component in the principal component set is obtained by normalizing the eigenvalue corresponding to each principal component in the principal component set.

[0057] The method for determining an agricultural irrigation scheme provided by an embodiment of the present invention determines the weight of each principal component by standardizing the eigenvalues ​​corresponding to the principal components, which helps to reasonably allocate the influence of different principal components in the comprehensive benefit score. The eigenvalue reflects the contribution of each principal component in explaining the variance of the original data. Therefore, through standardization, the eigenvalue can be converted into a relative proportion to ensure that the sum of the weights is 1. The beneficial effect of this process is that it objectively measures the importance of each principal component in a data-driven manner, avoids the deviation that may be caused by subjective weight allocation, and maximizes the explanatory power of the principal component, making the comprehensive benefit evaluation more scientific and reliable.

[0058] The agricultural irrigation scheme determination device provided by the present invention is described below. The agricultural irrigation scheme determination device described below and the agricultural irrigation scheme determination method described above can be referenced to each other.

[0059] FIG2 is a schematic diagram of the structure of the agricultural irrigation scheme determination device provided by the present invention. As shown in FIG2 , the agricultural irrigation scheme determination device includes: A prediction module 210 is used to input the simulated irrigation scheme set into the prediction layer in the irrigation scheme prediction model to obtain an irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; A comprehensive benefit score determination module 220, which is used to determine the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on the key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set; The agricultural irrigation scheme determination module 230 is used to determine the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme; The irrigation scheme prediction model is obtained by training based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0060] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the method for determining an agricultural irrigation scheme, the method comprising: inputting a simulated irrigation scheme set into a prediction layer in an irrigation scheme prediction model, obtaining an irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; based on the key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set, determining the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set; determining the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme; wherein the irrigation scheme prediction model is trained based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0061] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, 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, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0062] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the agricultural irrigation scheme determination method provided by the above-mentioned methods, the method including: inputting a simulated irrigation scheme set into a prediction layer in an irrigation scheme prediction model to obtain an irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds one-to-one to each simulated irrigation scheme in the simulated irrigation scheme set; each of the irrigation scheme prediction results includes a key performance indicator set; based on the key performance indicator set of each of the irrigation scheme prediction results in the irrigation scheme prediction result set, determining the comprehensive benefit score of each of the irrigation scheme prediction results in the irrigation scheme prediction result set; determining the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme; wherein the irrigation scheme prediction model is trained based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0063] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the agricultural irrigation scheme determination method provided by the above-mentioned methods, the method comprising: inputting a simulated irrigation scheme set into a prediction layer in an irrigation scheme prediction model to obtain an irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds one-to-one to each simulated irrigation scheme in the simulated irrigation scheme set; each of the irrigation scheme prediction results includes a key performance indicator set; based on the key performance indicator set of each of the irrigation scheme prediction results in the irrigation scheme prediction result set, determining a comprehensive benefit score for each of the irrigation scheme prediction results in the irrigation scheme prediction result set; determining the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme; wherein the irrigation scheme prediction model is trained based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

[0064] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0065] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining an agricultural irrigation scheme, characterized in that: include: Inputting the simulated irrigation scheme set into the prediction layer in the irrigation scheme prediction model, obtaining the irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; Determine a comprehensive benefit score for each irrigation scheme prediction result in the irrigation scheme prediction result set based on a key performance indicator set for each irrigation scheme prediction result in the irrigation scheme prediction result set; The simulated irrigation scheme corresponding to the prediction result of the irrigation scheme with the highest comprehensive benefit score is determined as the agricultural irrigation scheme; The irrigation scheme prediction model is obtained by training based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

2. The method for determining an agricultural irrigation scheme according to claim 1, characterized in that: Before inputting the simulated irrigation plan set into the prediction layer in the irrigation plan prediction model, the method includes: The preset agricultural configuration data set is input into the simulation layer in the irrigation plan prediction model to obtain a simulated irrigation plan set output by the simulation layer. The simulation layer is used to determine each preset agricultural configuration data in the preset agricultural configuration data set as a simulated irrigation plan to obtain a simulated irrigation plan set.

3. The method for determining an agricultural irrigation scheme according to claim 1, characterized in that: Determining the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on the key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set includes: The key performance indicator set of the prediction results of each irrigation scheme is standardized to obtain a standardized performance indicator matrix; Based on the standardized performance indicator matrix, a covariance matrix is ​​constructed; Performing eigenvalue decomposition on the covariance matrix to obtain an eigenvalue set and an eigenvector set, wherein each eigenvalue in the eigenvalue set corresponds to each eigenvector in the eigenvector set in one-to-one correspondence; Determining a principal component set from the eigenvector set based on the sorting results of the eigenvalues ​​in the eigenvalue set; Based on the standardized performance indicator matrix and the principal component set, determining the score of each irrigation scheme prediction result on each principal component in the principal component set; Based on the score of each irrigation scheme prediction result on each principal component in the principal component set and the weight of each principal component in the principal component set, the comprehensive benefit score of each irrigation scheme prediction result is determined.

4. The method for determining an agricultural irrigation scheme according to claim 3, characterized in that: The key performance indicator set of each irrigation scheme prediction result is standardized based on the following standardized formula: ； in, Indicates i The irrigation scheme prediction results are in j The original values ​​of the key performance indicators, The first j The mean of the key performance indicators, The first j The standard deviation of the key performance indicators, Indicates the normalized value.

5. The method for determining an agricultural irrigation scheme according to claim 3, characterized in that: The covariance matrix C is constructed based on the following formula: ； in, represents the transpose of the standardized performance indicator matrix, Z represents the standardized performance indicator matrix, and n represents the number of irrigation scheme prediction results.

6. The method for determining an agricultural irrigation scheme according to claim 3, characterized in that: The weight of each principal component in the principal component set is obtained based on the normalization of the eigenvalue corresponding to each principal component in the principal component set.

7. An agricultural irrigation scheme determination device, characterized in that: include: A prediction module, which is used to input the simulated irrigation scheme set into the prediction layer in the irrigation scheme prediction model, and obtain the irrigation scheme prediction result set output by the prediction layer, wherein each irrigation scheme prediction result in the irrigation scheme prediction result set corresponds to each simulated irrigation scheme in the simulated irrigation scheme set; each irrigation scheme prediction result includes a key performance indicator set; A comprehensive benefit score determination module, which is used to determine the comprehensive benefit score of each irrigation scheme prediction result in the irrigation scheme prediction result set based on a key performance indicator set of each irrigation scheme prediction result in the irrigation scheme prediction result set; An agricultural irrigation scheme determination module is used to determine the simulated irrigation scheme corresponding to the irrigation scheme prediction result with the highest comprehensive benefit score as the agricultural irrigation scheme; The irrigation scheme prediction model is obtained by training based on sample irrigation schemes and irrigation scheme prediction result labels corresponding to the sample irrigation schemes.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the agricultural irrigation scheme determination method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining an agricultural irrigation plan according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining an agricultural irrigation plan according to any one of claims 1 to 6 is implemented.

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