Irrigation area measurement and control integrated gate intelligent control system and method thereof

Abstract

The invention discloses an irrigation area measurement and control integrated gate intelligent control system and a method thereof, and relates to the field of gate control. The irrigation process of a current to-be-controlled irrigation area is divided into multiple stages, and mapping equations of various types of state parameters of each stage are constructed; the opening parameter of each gate in each stage is dynamically adjusted, and it is guaranteed that the irrigation effect of the whole irrigation process of the current irrigation area to be controlled is optimal; the method comprises the following steps: carrying out multiple times of iterative adjustment on an opening parameter of each gate at the end moment of a traversal irrigation stage of a current irrigation area by adopting a wild horse optimization algorithm; errors between various types of state parameters capable of being adjusted and corresponding ideal values at the end moment of the current irrigation area traversal irrigation stage are smaller and smaller, namely, the irrigation effect of the current irrigation area traversal irrigation stage is better and better.

Description

Technical Field

[0001] The present invention belongs to the field of gate control, and in particular, relates to an intelligent control system and method for an irrigation area measurement and control integrated gate. Background Art

[0002] During the irrigation process, some areas may have different demands for irrigation water at different stages of time. In traditional irrigation, the gate opening is not adjusted according to different stages, which may cause water accumulation in some areas of the irrigation area due to excessive water, and drought in other areas due to insufficient water. In addition, previous irrigation technologies cannot perform fine management of different stages, making it difficult to achieve the best results in the entire irrigation process. Summary of the invention

[0003] In view of the problems in the related technology, the present invention proposes an irrigation area measurement and control integrated gate intelligent control system and method thereof to overcome the above-mentioned technical problems existing in the existing related technology.

[0004] To solve the above technical problems, the present invention is achieved through the following technical solutions: The present invention is an intelligent control method for an irrigation area measurement and control integrated gate, comprising the following steps: S1. Setting several types of state parameter types that can reflect the irrigation area to obtain an irrigation area state parameter type set; S2. Collect various types of adjustable state parameter data, gate opening parameters and various types of non-adjustable state parameter data of each gate in the current controlled irrigation area within multiple historical periods in the control decision interval in cooperation with the irrigation area state parameter type set to construct a final gate state parameter mapping equation matrix set; S3, collecting adjustable state parameter data, unadjustable state parameter change equations and gate opening parameters of each type of gates in the current irrigation area during the irrigation stage of the current irrigation area; S4, input the data collected in S3 into the final gate state parameter mapping equation matrix for centralized mapping and loop through each current irrigation area during the irrigation stage, and adjust the opening parameters of each gate of each current irrigation area during the irrigation stage by setting the ideal value of each type of adjustable state parameter data corresponding to each gate at the end time of each current irrigation area during the irrigation stage, so as to obtain the final opening parameter matrix of the current irrigation gate; This scheme divides the irrigation process of the current irrigation area to be controlled into multiple stages, constructs mapping equations of various types of state parameters in each stage, and dynamically adjusts the opening parameters of each gate in each stage, thereby ensuring that the irrigation effect achieved in the entire irrigation process of the current irrigation area to be controlled is optimal.

[0005] Preferably, the S1 comprises the following steps: S11, setting several types of adjustable state parameter types and non-adjustable state parameter types that can reflect the irrigation area, the irrigation area gates, and the surrounding environment of the irrigation area, and obtaining a first irrigation gate state parameter type set and a second irrigation gate state parameter type set; setting the current irrigation area to be controlled, obtaining each gate in the current irrigation area to be controlled, and obtaining the current irrigation area gate set; S12, setting the gate control decision interval and the current irrigation area irrigation cycle in coordination with the current irrigation area to be controlled and the current irrigation area gate set; Since the state of the gate is composed of multiple parameters, in this scheme, several parameter types that have an impact on the gate opening control are selected from the parameters of multiple gates, providing a basis for the subsequent collection of the gate parameters; since at different locations in the irrigation area, both the soil moisture content of the surrounding environment and the water storage capacity of the channel are greatly different: for example, the water storage capacity of the upstream of the channel is higher, and the water storage capacity of the downstream is less. Based on this, in this scheme, different types of strategies are used to control each gate in the current irrigation area to be controlled, so that the control is more precise; in addition, since the water demand around the irrigation area is different in different time periods, the control interval of each gate in the current irrigation cycle of the irrigation area is further guaranteed to ensure the precision of the control.

[0006] Preferably, S2 comprises the following steps: S21, in conjunction with the irrigation area state parameter type set, the gate control decision interval, the current irrigation area irrigation cycle, the first irrigation gate state parameter type set and the second irrigation gate state parameter type set, collect various types of adjustable state parameter data corresponding to the initial and end times of the control decision interval for each gate in the current irrigation area to be controlled within multiple groups of historical cycles, the gate opening parameters and the change equations of various types of non-adjustable state parameter data between the initial and end times, and obtain the first current historical state parameter matrix, the second current historical state parameter matrix and the current historical gate opening parameter matrix; S22, using the first current historical state parameter matrix, the second current historical state parameter matrix and the current historical gate opening parameter matrix to construct mapping equations of various types of adjustable state parameters corresponding to each gate in the current irrigation district gate set, and obtain a final gate state parameter mapping equation matrix set; This scheme establishes mapping equations between various adjustable state parameters corresponding to the initial and end times of each control decision interval for each gate in the current irrigation area to be controlled, so that various adjustable state parameters at the corresponding end time can be obtained according to the various adjustable state parameters at the initial time of each control decision interval in the current irrigation area irrigation cycle, the change equations of various types of non-adjustable state parameters, and the opening parameters before and after the gate. In order to determine whether it is necessary to adjust the opening parameters before and after the gate, various adjustable state parameters at the corresponding end time can reach the optimal value, thereby achieving the best irrigation effect on the surrounding area of ​​the current irrigation area during the entire current irrigation cycle.

[0007] Preferably, the S22 comprises the following steps: S221, constructing initial mapping equations of various types of adjustable state parameters corresponding to each gate in the current irrigation district gate set in conjunction with the first current historical state parameter matrix, the second current historical state parameter matrix, and the current historical gate opening parameter matrix, to obtain an initial gate state parameter mapping equation matrix set; S222, substitute the various types of adjustable state parameters at the initial moment of each gate control decision interval in the first current historical state parameter matrix, the change equations of various types of non-adjustable state parameter data within each gate control decision interval in the second current historical state parameter matrix, and the gate opening parameters at the initial moment and the end moment of each gate control decision interval in the current historical gate opening parameter matrix into the initial gate state parameter mapping equation corresponding to the initial gate state parameter mapping equation matrix set for mapping, and obtain the historical moment adjustable state parameter mapping data matrix; Calculate the error between the adjustable state parameter mapping data matrix at the historical moment and the adjustable state parameter at the end of each gate control decision interval corresponding to each gate in the first current historical state parameter matrix to obtain the current historical state parameter initial mapping error data matrix set; S223, setting a gate control decision interval state parameter mapping error threshold; when there is mapping error data greater than or equal to the gate control decision interval state parameter mapping error threshold in the current historical state parameter initial mapping error data matrix set, adjusting the initial gate state parameter mapping equation corresponding to the mapping error data until there is no mapping error data greater than or equal to the gate control decision interval state parameter mapping error threshold in the current historical state parameter initial mapping error data matrix set, and obtaining a final gate state parameter mapping equation matrix set; otherwise, no adjustment is required, and the initial gate state parameter mapping equation matrix set is used as the final gate state parameter mapping equation matrix set; By using the least squares principle, the combination relationship of various types of state parameter variables is abstracted, such as product relationship and power exponential relationship (that is, one independent variable is used as the power exponent of another independent variable), etc. Based on this method, various types of state parameter variables are combined into a mapping equation, so that after the collected multiple gate state parameter data are operated in this combination method, the operation result can be consistent with the value of the actual data corresponding to the mapping equation dependent variable, thereby realizing the mapping from various types of state parameter variables to the mapping equation dependent variable; Based on the above, in this scheme, the change equations of various types of state parameters that cannot be adjusted, the opening parameters of the gate at the initial time and the end time of the control decision interval The number and each type of adjustable state parameter data at the initial moment of the control decision interval are used as independent variables, and each type of adjustable state parameter data at the end moment of the control decision interval is used as a dependent variable, thereby realizing the mapping from the change equations of multiple types of non-adjustable state parameters, the opening parameters of the gate at the initial moment and the end moment of the control decision interval, and each type of adjustable state parameter data at the initial moment of the control decision interval to each type of adjustable state parameter data at the end moment of the control decision interval, providing a mapping tool for the subsequent acquisition of the corresponding end moment data based on the data at the initial moment of the control decision interval, so as to further adjust the opening parameters of the gate; In addition, by substituting the collected historical data into each constructed initial gate state parameter mapping equation, the mapping accuracy of each initial gate state parameter mapping equation is detected to determine whether the initial gate state parameter mapping equation needs to be adjusted.

[0008] Preferably, S3 comprises the following steps: S31, using the gate control decision interval to divide the current irrigation area irrigation cycle into stages to obtain a current irrigation area irrigation stage set; traversing the current irrigation area irrigation stage set and recording the current traversed current irrigation area irrigation stage as the current irrigation area traversed irrigation stage; In conjunction with the first flooding gate state parameter type set, the current irrigation area gate set and the final gate state parameter mapping equation matrix set, each type of adjustable state parameter data of each current irrigation area gate corresponding to the initial moment of the current irrigation area traversal flooding stage is collected to obtain the current traversal initial moment adjustable state parameter matrix; and then in conjunction with the second flooding gate state parameter type set, each type of non-adjustable state parameter data corresponding to each current irrigation area gate in the current irrigation area traversal flooding stage is obtained. The state parameter change equation matrix of the non-adjustable state parameter of the current traversal flooding stage is obtained; S32, collecting the opening parameters of each current irrigation district gate corresponding to the initial moment of the current irrigation district traversal irrigation stage, and presetting the opening parameters of each current irrigation district gate corresponding to the end moment of the current irrigation district traversal irrigation stage, to obtain the initial opening parameter set of the gate in the current traversal irrigation stage; As the irrigation time progresses, each current irrigation area irrigation stage will be passed; by traversing the current irrigation area irrigation stage set, it is used to map various types of adjustable state parameter data at the end time according to various types of adjustable and non-adjustable state parameter data at the initial moment of each current irrigation area irrigation stage, so as to adjust the gate opening parameters according to the mapping results, so as to achieve the best irrigation effect in the entire current irrigation area irrigation cycle; based on this, by collecting the current traversal initial moment adjustable state parameter matrix, the current traversal irrigation stage non-adjustable state parameter change equation matrix and the current traversal irrigation stage gate initial opening parameter set, data support is provided for the subsequent mapping of various types of adjustable state parameter data at the end of each stage.

[0009] Preferably, in S31, obtaining the change equation of each type of state parameter data that cannot be adjusted corresponding to each current irrigation district gate in the current irrigation district traversal irrigation stage in cooperation with the second flooding gate state parameter type set includes the following steps: S311, setting a number of collection time points before the current irrigation area traversal irrigation phase begins to obtain a current historical collection time point set; collecting each type of unadjustable state parameter data corresponding to each gate according to the current historical collection time point set and the second flooding gate state parameter type set to obtain a current historical unadjustable state parameter matrix set; S312, using the BP neural network model in conjunction with the current historical non-adjustable state parameter matrix set to predict each type of non-adjustable state parameter data corresponding to each gate at multiple time points in the current irrigation area during the irrigation phase, to obtain a current non-adjustable state parameter matrix set; Fitting the change equation of each type of unadjustable state parameter data corresponding to each gate in the current irrigation area traversal irrigation stage according to the current unadjustable state parameter matrix set to obtain the unadjustable state parameter change equation matrix of the current traversal irrigation stage; The BP neural network model can process various types of data, including numerical, categorical and sequential data. It can also be adjusted and optimized according to different problems and data sets. The performance of the model can be improved by adjusting parameters such as network structure, activation function and learning rate. It can automatically learn and extract features from input data without manual feature engineering, and can abstract input data layer by layer to obtain higher-level feature representation. Based on this, the BP neural network model is used in this scheme to predict each type of non-adjustable state parameter data corresponding to each gate at multiple time points in the current irrigation area during the irrigation stage, thereby ensuring the credibility of the prediction results.

[0010] Preferably, the S4 comprises the following steps: S41, inputting the adjustable state parameter matrix of the current traversal initial moment, the non-adjustable state parameter change equation matrix of the current traversal filling stage, and the initial gate opening parameter set of the current traversal filling stage into the corresponding mapping equation in the final gate state parameter mapping equation matrix set for mapping, to obtain the adjustable state parameter matrix of the current traversal final moment; S42, setting the ideal data corresponding to each type of adjustable state parameter data at the end of the irrigation stage of the current irrigation area, and obtaining the ideal value set of the adjustable state parameters at the end of the current stage; Adjust the initial opening parameter of each current irrigation area gate in the initial opening parameter set of the gate in the current traversal irrigation stage in conjunction with the ideal value set of the adjustable final state parameters in the current stage to obtain the final opening parameter set of the gate in the current traversal irrigation stage; S43, after the adjustment is completed, the next stage of the current irrigation area traversal irrigation stage is used as the current irrigation area traversal irrigation stage, and the final gate opening parameter set of the current irrigation area traversal irrigation stage is used as the opening parameter of each current irrigation area gate corresponding to the initial moment of the current irrigation area traversal irrigation stage; S31, S32, S41, S42 and S43 are repeated until the current irrigation area traversal irrigation stage is the last current irrigation area irrigation stage in the current irrigation area irrigation stage set; The final gate opening parameter set of the current traversal water filling stage obtained in each round of traversal is integrated to obtain the final opening parameter matrix of the current water filling gate; S44, setting the opening parameter of each gate corresponding to the irrigation of the current irrigation area to be controlled according to the final opening parameter matrix of the current irrigation gate; By adjusting the opening parameters of each gate at the end time of each current irrigation area traversal irrigation stage, the irrigation effect of each current irrigation area traversal irrigation stage reaches the local optimum, so that the adjustment of the opening parameters of each gate at the end time of the next stage is based on the premise that the irrigation effect of the previous stage reaches the local optimum; therefore, when all the current irrigation area traversal irrigation stages are completed, it can be guaranteed that the final irrigation effect reaches the optimum.

[0011] Preferably, in S42, adjusting the initial opening parameter of each current irrigation area gate in the current traversal irrigation stage gate initial opening parameter set in conjunction with the current stage adjustable final state parameter ideal value set comprises the following steps: S421, setting the value interval of the opening parameter of each current irrigation area gate at the end time in the initial gate opening parameter set of the current traversal irrigation stage, and obtaining the gate opening parameter value interval set at the end of the current traversal stage; Construct the wild horse population for adjusting the gate opening parameters at the end of the current traversal stage; set the maximum number of iterations of the wild horse population for adjusting the gate opening parameters at the end of the current traversal stage to And the current number of iterations is , respectively recorded as the maximum number of iterations for parameter adjustment and the current number of iterations for parameter adjustment; S422, adjusting the initial position of each wild horse in the wild horse population by setting the gate opening parameter at the end of the current traversal stage according to the gate opening parameter value interval set at the end of the current traversal stage, and obtaining a second initial position matrix; S423, constructing a fitness function for adjusting the wild horse population by using the gate opening parameter at the end of the current traversal stage; S424, start iteration, set the current iteration number of the parameter adjustment to 1 before iteration; in the first round of iteration, use the gate opening parameter of the current traversal stage to adjust the fitness function of the wild horse population to calculate the fitness value of the initial position of each wild horse in the second initial position matrix, and obtain a third fitness value set; use the maximum fitness value in the third fitness value set and the initial position of the corresponding wild horse as the third global optimal fitness and the third global optimal position respectively; update the initial position of each wild horse in the second initial position matrix according to the third global optimal fitness and the third global optimal position; after the update is completed, add 1 to the current iteration number of the parameter adjustment and enter the next round of iteration; In each other round of iteration, the fitness function of the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage is used to calculate the fitness value of the position of each wild horse in the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage updated in the previous round of iteration, and a fourth fitness value set is obtained; the maximum fitness value in the fourth fitness value set and the position of the corresponding wild horse are respectively used as the fourth global optimal fitness and the fourth global optimal position; the position of each wild horse in the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage updated in the previous round of iteration is updated according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, the current iteration number of the gate opening adjustment is increased by 1 and the next round of iteration is entered; S425, when When , stop the iteration and get the second final global optimal position; otherwise, continue to iterate until until the second final global optimal position is used as the final gate opening parameter set of the current traversal irrigation stage; The wild horse optimization algorithm can perform effective global search in the search space and find a better solution by simulating the life behaviors of wild horse populations, such as grazing, mating, and leadership. During the iteration process, it can perform local search near the current optimal solution to further optimize the quality of the solution and improve the convergence accuracy. By introducing adaptive mechanisms and random factors, it can effectively avoid premature convergence of the algorithm and improve the robustness of the algorithm. There are fewer parameters and it is easy to adjust and optimize. Based on this, the wild horse optimization algorithm is used to iteratively adjust the opening parameters of each gate at the end of the current irrigation area traversal irrigation stage for multiple times, and the error between various types of adjustable state parameters at the end of the current irrigation area traversal irrigation stage and the corresponding ideal value is used as the fitness function. Therefore, as the iteration proceeds, the error between various types of adjustable state parameters at the end of the current irrigation area traversal irrigation stage and the corresponding ideal value becomes smaller and smaller, that is, the irrigation effect of the current irrigation area traversal irrigation stage is getting better and better.

[0012] The intelligent control system of the integrated gate of the irrigation area measurement and control includes an irrigation area state parameter setting module, a current irrigation area gate acquisition module, a gate state parameter mapping equation construction module, a current traversal irrigation stage state parameter acquisition module and a current traversal stage gate opening parameter cyclic adjustment module.

[0013] The present invention has the following beneficial effects: 1. In the present invention, the irrigation process of the current irrigation area to be controlled is divided into multiple stages, and mapping equations of various types of state parameters in each stage are constructed to dynamically adjust the opening parameters of each gate in each stage, thereby ensuring that the irrigation effect achieved in the entire irrigation process of the current irrigation area to be controlled is optimal.

[0014] 2. In the present invention, different types of strategies are adopted to control each gate of the current irrigation area to be controlled, so that the control is more precise; in addition, since the water demand around the irrigation area is different in different time periods, the control interval of each gate in the current irrigation cycle of the irrigation area is further guaranteed to ensure the precision of the control.

[0015] 3. In the present invention, the multiple constant coefficients of the gate state parameter mapping equation to be adjusted are iteratively adjusted multiple times by adopting the wild horse optimization algorithm, and the mapping accuracy of the gate state parameter mapping equation to be adjusted is used as the fitness function; therefore, as the iteration proceeds, the mapping accuracy of the gate state parameter mapping equation to be adjusted becomes higher and higher, and finally meets the mapping requirements.

[0016] 4. In the present invention, the wild horse optimization algorithm is used to iteratively adjust the opening parameters of each gate at the end time of the current irrigation area traversal irrigation stage for multiple times, and the error between various types of adjustable state parameters at the end time of the current irrigation area traversal irrigation stage and the corresponding ideal value is used as the fitness function; therefore, as the iteration proceeds, the error between various types of adjustable state parameters at the end time of the current irrigation area traversal irrigation stage and the corresponding ideal value becomes smaller and smaller, that is, the irrigation effect of the current irrigation area traversal irrigation stage is getting better and better.

[0017] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a flow chart of the intelligent control method of the irrigation area measurement and control integrated gate of the present invention; Figure 2 A schematic diagram of a process for constructing a final gate state parameter mapping equation matrix set according to the present invention; Figure 3 A schematic diagram of a flow chart of adjusting gate opening parameters according to the present invention; Figure 4 It is a module schematic diagram of the intelligent control system of the irrigation area integrated measurement and control gate of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the invention to clearly and completely describe the technical solutions in the embodiments of the invention. Obviously, the described embodiments are only part of the embodiments of the invention, not all of the embodiments. Based on the embodiments in the invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the invention.

[0021] Embodiment 1 See also Figure 1-3 This embodiment is an intelligent control method for an irrigation area integrated gate, comprising the following steps: S1. Setting several types of state parameter types that can reflect the irrigation area to obtain an irrigation area state parameter type set; The S1 comprises the following steps: S11, setting several types of adjustable state parameter types and non-adjustable state parameter types that can reflect the irrigation area, the irrigation area gate, and the surrounding environment of the irrigation area, and obtaining a first irrigation gate state parameter type set and a second irrigation gate state parameter type set; the first irrigation gate state parameter type set includes a channel water storage parameter type, a soil moisture parameter type, a gate water level parameter type, and a gate flow parameter type; the second irrigation gate state parameter type set includes a rainfall parameter type and a disaster flag parameter type (such as heavy rain: 1, drought: 2), etc.; setting the current irrigation area to be controlled, obtaining each gate in the current irrigation area to be controlled, and obtaining the current irrigation area gate set; S12, setting the gate control decision interval and the current irrigation area irrigation cycle in coordination with the current irrigation area to be controlled and the current irrigation area gate set; S2. Collect various types of adjustable state parameter data, gate opening parameters and various types of non-adjustable state parameter data of each gate in the current controlled irrigation area within multiple historical periods in the control decision interval in cooperation with the irrigation area state parameter type set to construct a final gate state parameter mapping equation matrix set; The S2 comprises the following steps: S21, in conjunction with the irrigation area state parameter type set, the gate control decision interval, the current irrigation area irrigation cycle, the first irrigation gate state parameter type set and the second irrigation gate state parameter type set, collect various types of adjustable state parameter data corresponding to the initial and end times of the control decision interval for each gate in the current irrigation area to be controlled within multiple groups of historical cycles, the gate opening parameters and the change equations of various types of non-adjustable state parameter data between the initial and end times, and obtain a first current historical state parameter matrix a , the second current historical state parameter matrix And the current historical gate opening parameter matrix ; They are as follows, ; ; ; ; ; in, a ij , Respectively represent the collected i Group historical period j The adjustable state parameter matrix and the non-adjustable state parameter matrix corresponding to each gate; Indicates the collected i Group historical period j The opening parameter set corresponding to each gate; , Respectively a ij Middle k The control decision interval initial moment and end moment correspond to the k 1 types of state parameters that can be adjusted; express Middle k During the control decision interval k 1 Equations for the variation of state parameters of a type that cannot be adjusted; , Respectively Middle k The gate opening parameters corresponding to the initial and end times of the control decision interval; Indicates the total number of gates in the current irrigation area to be controlled; Indicates the total number of groups of state parameters collected for the current irrigation area to be controlled within the historical period; , Indicates the total number of state parameter types that can be adjusted and the total number of state parameter types that cannot be adjusted; Indicates the total number of gate control decision intervals divided into multiple groups of historical periods; S22, using the first current historical state parameter matrix, the second current historical state parameter matrix and the current historical gate opening parameter matrix to construct mapping equations of various types of adjustable state parameters corresponding to each gate in the current irrigation district gate set, and obtain a final gate state parameter mapping equation matrix set; The S22 comprises the following steps: S221, constructing initial mapping equations of various types of adjustable state parameters corresponding to each gate in the current irrigation area gate set in conjunction with the first current historical state parameter matrix, the second current historical state parameter matrix, and the current historical gate opening parameter matrix, and obtaining an initial gate state parameter mapping equation matrix set , b j Indicates j The initial gate state parameter mapping equation matrix corresponding to each gate is as follows: ; in, express b j Middle k The control decision interval k 1 The mapping equations of the types of adjustable state parameters are as follows: ; in, for The dependent variable, The corresponding control decision interval ends at k 1 Types of adjustable state parameter data; for The mapping relationship is used to combine the independent variables, such as product combination, division combination, etc. for No. independent variable, indicating The corresponding Equations for the variation of state parameters of a type that cannot be adjusted; , , They are No. , and The independent variables represent The corresponding control decision interval at the initial time k 1 types of adjustable status parameter data, The opening parameters of the corresponding gate at the initial and end times of the control decision interval; S222, substitute the various types of adjustable state parameters at the initial moment of each gate control decision interval in the first current historical state parameter matrix, the various types of non-adjustable state parameter data in each gate control decision interval in the second current historical state parameter matrix, and the gate opening parameters at the initial moment and the end moment of each gate control decision interval in the current historical gate opening parameter matrix into the initial gate state parameter mapping equation corresponding to the initial gate state parameter mapping equation matrix set for mapping, and obtain the historical moment adjustable state parameter mapping data matrix ;as follows, ; ; in, Indicates the mapped i Group historical period j The adjustable state parameter matrix corresponding to each gate; express Middle k The control decision interval ends at the corresponding k 1 The adjustable state parameters obtained by mapping of the types; Calculate the error between the adjustable state parameter mapping data matrix at the end of the control decision interval of each gate corresponding to each gate in the first current historical state parameter matrix, and obtain the current historical state parameter initial mapping error data matrix set. , Indicates the mapping data matrix of the adjustable state parameters of the historical moment and the first current historical state parameter matrix j The error data matrix between the adjustable state parameters at the end of each gate control decision interval corresponding to each gate is as follows: ; in, express b j Middle k The control decision interval k 1 The error data between the mapping data of the mapping equation of the state parameter that can be adjusted and the corresponding data in the first current historical state parameter matrix; the calculation formula is as follows, ; S223, setting a gate control decision interval state parameter mapping error threshold; when there is mapping error data greater than or equal to the gate control decision interval state parameter mapping error threshold in the current historical state parameter initial mapping error data matrix set, adjusting the initial gate state parameter mapping equation corresponding to the mapping error data until there is no mapping error data greater than or equal to the gate control decision interval state parameter mapping error threshold in the current historical state parameter initial mapping error data matrix set, and obtaining a final gate state parameter mapping equation matrix set; otherwise, no adjustment is required, and the initial gate state parameter mapping equation matrix set is used as the final gate state parameter mapping equation matrix set; The adjustment of the initial gate state parameter mapping equation corresponding to the mapping error data in S223 includes the following steps: S2231, taking the initial gate state parameter mapping equation corresponding to the mapping error data in the current historical state parameter initial mapping error data matrix set in S223 that is greater than or equal to the gate control decision interval final state parameter mapping error threshold as the gate state parameter mapping equation to be adjusted; Set the value intervals of several constant coefficients of the gate state parameter mapping equation to be adjusted to obtain a gate state parameter mapping constant coefficient value interval set c 1 , several constant coefficients of the gate state parameter mapping equation to be adjusted include the coefficient of the independent variable and the power exponential coefficients of each independent variable, etc.; c 1 as follows, ; in, , They represent the first i The lower and upper limits of the constant coefficients, Represents the total number of constant coefficients of the gate state parameter mapping equation to be adjusted; S2232, constructing a gate state parameter mapping equation to adjust the wild horse population; setting the maximum number of iterations of the gate state parameter mapping equation to adjust the wild horse population is And the current number of iterations is , respectively recorded as the maximum number of iterations of gate parameter adjustment and the current number of iterations of gate parameter adjustment; the gate state parameter mapping equation adjusts the search space dimension of the wild horse population and same; S2233, generating a gate state parameter mapping equation according to the gate state parameter mapping constant coefficient value interval set, adjusting the initial position of each wild horse in the wild horse population, and obtaining a first initial position matrix ;as follows, ; in, The gate state parameter mapping equation adjusts the wild horse population j The initial position of the wild horse is in the first i The position component in the dimension of constant coefficients, d 1 The gate state parameter mapping equation adjusts the size of the wild horse population; the generation formula is as follows, ; In the formula, rand 1ji Indicates for Generate a random number between 0 and 1; S2234, construct the gate state parameter mapping equation to adjust the fitness function of the wild horse population ;as follows, ; In the formula, Indicates that a set of constant coefficients obtained in each round of iteration is substituted into the gate state parameter mapping equation to be adjusted, and then the corresponding data in the first current historical state parameter matrix, the second current historical state parameter matrix and the current historical gate opening parameter matrix in S222 are substituted into the gate state parameter mapping equation to be adjusted for mapping to obtain the error between the mapping data and the actual data of the corresponding first current historical state parameter matrix; S2235, start iteration, before iteration, set the current iteration number of the gate parameter adjustment to 1; in the first round of iteration, use the gate state parameter mapping equation to adjust the fitness function of the wild horse population Calculate the fitness value of the initial position of each wild horse in the first initial position matrix to obtain a first fitness value set; use the maximum fitness value in the first fitness value set and the initial position of the corresponding wild horse as the first global optimal fitness and the first global optimal position respectively; update the initial position of each wild horse in the first initial position matrix according to the first global optimal fitness and the first global optimal position; after the update is completed, add 1 to the current iteration number of the gate parameter adjustment and enter the next round of iteration; In each other round of iteration, the gate state parameter mapping equation is used to adjust the fitness function of the wild horse population. Calculate the fitness value of the gate state parameter mapping equation updated in the previous round of iterations to adjust the position of each wild horse in the wild horse population, and obtain a second fitness value set; use the maximum fitness value in the second fitness value set and the position of the corresponding wild horse as the second global optimal fitness and the second global optimal position respectively; update the gate state parameter mapping equation updated in the previous round of iterations to adjust the position of each wild horse in the wild horse population according to the second global optimal fitness and the second global optimal position; after the update is completed, add 1 to the current iteration number of the gate parameter adjustment and enter the next round of iterations; S2236, when When , stop the iteration and get the first final global best fitness and the first final global best position; otherwise, continue to iterate until until the time; using the first final global optimal fitness as the current historical optimized state parameter mapping error data; When the current historical optimized state parameter mapping error data is less than the gate control decision interval state parameter mapping error threshold, substitute the various position components of the first final global optimal position into the gate state parameter mapping equation to be adjusted to obtain the optimized gate state parameter mapping equation; use the optimized gate state parameter mapping equation to replace the corresponding initial gate state parameter mapping equation in the initial gate state parameter mapping equation matrix set, and the adjustment is completed; otherwise, return to S2235 to continue iterating until the current historical optimized state parameter mapping error data is less than the gate control decision interval state parameter mapping error threshold; The Mustang optimization algorithm is used to iteratively adjust multiple constant coefficients of the gate state parameter mapping equation to be adjusted, and the mapping accuracy of the gate state parameter mapping equation to be adjusted is used as the fitness function; therefore, as the iteration proceeds, the mapping accuracy of the gate state parameter mapping equation to be adjusted becomes higher and higher, and finally the mapping requirements are met; S3, collecting adjustable state parameter data, unadjustable state parameter change equations and gate opening parameters of each type of gates in the current irrigation area during the irrigation stage of the current irrigation area; The S3 comprises the following steps: S31, using the gate control decision interval to divide the current irrigation area irrigation cycle into stages to obtain a current irrigation area irrigation stage set; traversing the current irrigation area irrigation stage set and recording the current traversed current irrigation area irrigation stage as the current irrigation area traversed irrigation stage; In conjunction with the first flooding gate state parameter type set, the current irrigation district gate set and the final gate state parameter mapping equation matrix set, the adjustable state parameter data of each type of each current irrigation district gate corresponding to the initial moment of the current irrigation district traversal flooding phase is collected to obtain the current traversal initial moment adjustable state parameter matrix ; Then, in conjunction with the second flooding gate state parameter type set, obtain the change equation of each type of state parameter data that cannot be adjusted corresponding to each current irrigation gate in the current irrigation area traversal irrigation stage, and obtain the change equation matrix of the non-adjustable state parameter in the current traversal irrigation stage ; , They are as follows: ; ; in, , They represent the first i The current irrigation area gate corresponds to the j The types of adjustable state parameter data and the number of times the current irrigation area is traversed during the irrigation phase i The current irrigation area gate corresponds to the j The variation equation of the state parameter data of the type that cannot be adjusted; In S31, obtaining the change equation of each type of state parameter data that cannot be adjusted corresponding to each current irrigation district gate in the current irrigation district traversal irrigation stage in cooperation with the second irrigation gate state parameter type set includes the following steps: S311, setting a number of collection time points before the current irrigation area traversal irrigation phase begins to obtain a current historical collection time point set; collecting each type of unadjustable state parameter data corresponding to each gate according to the current historical collection time point set and the second flooding gate state parameter type set to obtain a current historical unadjustable state parameter matrix set; S312, using the BP neural network model in conjunction with the current historical non-adjustable state parameter matrix set to predict each type of non-adjustable state parameter data corresponding to each gate at multiple time points in the current irrigation area during the irrigation phase, to obtain a current non-adjustable state parameter matrix set; Fitting the change equation of each type of unadjustable state parameter data corresponding to each gate in the current irrigation area traversal irrigation stage according to the current unadjustable state parameter matrix set to obtain the unadjustable state parameter change equation matrix of the current traversal irrigation stage; S32, collecting the opening parameters of each current irrigation district gate corresponding to the initial moment of the current irrigation district traversal irrigation stage, and presetting the opening parameters of each current irrigation district gate corresponding to the end moment of the current irrigation district traversal irrigation stage, to obtain the initial opening parameter set of the gate in the current traversal irrigation stage ;as follows, ; in, , They represent the initial moment of the irrigation phase of the current irrigation area. i The current irrigation area gate opening parameters and the end time i The initial opening parameters of the current irrigation area gate; S4, input the data collected in S3 into the final gate state parameter mapping equation matrix for centralized mapping and loop through each current irrigation area during the irrigation stage, and adjust the opening parameters of each gate of each current irrigation area during the irrigation stage by setting the ideal value of each type of adjustable state parameter data corresponding to each gate at the end time of each current irrigation area during the irrigation stage, so as to obtain the final opening parameter matrix of the current irrigation gate; The S4 comprises the following steps: S41, input the adjustable state parameter matrix of the current traversal initial moment, the non-adjustable state parameter change equation matrix of the current traversal filling stage, and the initial gate opening parameter set of the current traversal filling stage into the corresponding mapping equation in the final gate state parameter mapping equation matrix set for mapping, and obtain the adjustable state parameter matrix of the current traversal final moment ;as follows, ; in, Indicates the time at which the current irrigation area traverses the irrigation phase obtained by mapping. i The current irrigation area gate corresponds to the j Types of adjustable state parameter data; S42: Set the ideal data corresponding to each type of adjustable state parameter data at the end of the irrigation phase of the current irrigation area, and obtain the ideal value set of the adjustable state parameter at the end of the current phase. , Indicates the end time of the irrigation phase of the current irrigation area. j The ideal data corresponding to the adjustable state parameter data of the types; Adjust the initial opening parameter of each current irrigation area gate in the initial opening parameter set of the gate in the current traversal irrigation stage in conjunction with the ideal value set of the adjustable final state parameters in the current stage to obtain the final opening parameter set of the gate in the current traversal irrigation stage; In S42, adjusting the initial opening parameter of each current irrigation area gate in the current traversal irrigation stage gate initial opening parameter set in conjunction with the current stage adjustable final state parameter ideal value set includes the following steps: S421, set the value interval of the opening parameter of each current irrigation area gate at the end time in the initial gate opening parameter set of the current traversal irrigation stage, and obtain the value interval set of the gate opening parameter at the end of the current traversal stage c 2 ,as follows, ; in, , Respectively represent the number of irrigation stages in the current irrigation area. i The lower limit and upper limit of the opening parameter of the current irrigation area gate at the end time; Construct the wild horse population for adjusting the gate opening parameters at the end of the current traversal stage; set the maximum number of iterations of the wild horse population for adjusting the gate opening parameters at the end of the current traversal stage to And the current number of iterations is , respectively recorded as the maximum number of iterations of parameter adjustment and the current number of iterations of parameter adjustment; the gate opening parameter of the current traversal stage adjusts the search space dimension of the wild horse population and same; S422, according to the gate opening parameter value interval set of the current traversal stage, the gate opening parameter of the current traversal stage is set to adjust the initial position of each wild horse in the wild horse population, and obtain a second initial position matrix ;as follows, ; in, Indicates that the gate opening parameter of the current traversal stage is adjusted in the wild horse population. j The initial position of the wild horse is the first in the current irrigation area during the irrigation phase. i The position component of the current irrigation area gate opening parameter dimension at the end time, d 2 Indicates that the gate opening parameter at the end of the current traversal stage adjusts the size of the wild horse population; S423, constructing the fitness function of the wild horse population by adjusting the gate opening parameters at the end of the current traversal stage ;as follows, ; In the formula, is a positive number, indicating a protection parameter, which is used to ensure that the denominator of the fitness function of the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage is not 0; S424, start iteration, before iteration, set the current number of iterations to 1; in the first round of iteration, use the gate opening parameter of the current traversal stage to adjust the fitness function of the wild horse population Calculate the fitness value of the initial position of each wild horse in the second initial position matrix to obtain a third fitness value set; use the maximum fitness value in the third fitness value set and the initial position of the corresponding wild horse as the third global optimal fitness and the third global optimal position respectively; update the initial position of each wild horse in the second initial position matrix according to the third global optimal fitness and the third global optimal position; after the update is completed, add 1 to the current iteration number of the open parameter adjustment and enter the next round of iteration; In each other round of iteration, the fitness function of the wild horse population is adjusted by using the gate opening parameter at the end of the current traversal stage. Calculate the fitness value of the position of each wild horse in the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage updated in the previous iteration process to obtain a fourth fitness value set; use the maximum fitness value in the fourth fitness value set and the position of the corresponding wild horse as the fourth global optimal fitness and the fourth global optimal position respectively; update the position of each wild horse in the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage updated in the previous iteration process according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, increase the current iteration number of the gate opening adjustment by 1 and enter the next iteration; S425, when When , stop the iteration and get the second final global optimal position; otherwise, continue to iterate until until the second final global optimal position is used as the final gate opening parameter set of the current traversal irrigation stage; S43, after the adjustment is completed, the next stage of the current irrigation area traversal irrigation stage is used as the current irrigation area traversal irrigation stage, and the final gate opening parameter set of the current irrigation area traversal irrigation stage is used as the opening parameter of each current irrigation area gate corresponding to the initial moment of the current irrigation area traversal irrigation stage; S31, S32, S41, S42 and S43 are repeated until the current irrigation area traversal irrigation stage is the last current irrigation area irrigation stage in the current irrigation area irrigation stage set; The final gate opening parameter set of the current traversal water filling stage obtained in each round of traversal is integrated to obtain the final opening parameter matrix of the current water filling gate; S44. In conjunction with the final opening parameter matrix of the current irrigation gate, the opening parameter of each gate corresponding to the irrigation of the current irrigation area to be controlled is set.

[0022] Embodiment 2 See also Figure 4This embodiment discloses an intelligent control system for an irrigation district integrated gate measurement and control, and the system can implement the method of the above embodiment, including an irrigation district state parameter setting module, a current irrigation district regional gate acquisition module, a gate state parameter mapping equation construction module, a current traversal irrigation stage state parameter acquisition module, and a current traversal stage end gate opening parameter cyclic adjustment module; The irrigation area state parameter setting module sets several types of state parameters that can reflect the irrigation area, and obtains an irrigation area state parameter type set; The current irrigation area gate acquisition module acquires each gate in the current irrigation area to be controlled to obtain the current irrigation area gate set; The gate state parameter mapping equation construction module collects various types of adjustable state parameter data corresponding to the initial and end times of the control decision interval for each gate in the current irrigation area to be controlled within multiple groups of historical periods, the gate opening parameters, and the change equations of various types of non-adjustable state parameter data between the initial and end times to construct a final gate state parameter mapping equation matrix set by cooperating with the irrigation area state parameter type set and the current irrigation area gate set; The current traversal irrigation stage state parameter acquisition module cooperates with the current irrigation area gate set and the final gate state parameter mapping equation matrix set to collect adjustable state parameter data, unadjustable state parameter change equations and gate opening parameters of each type of current irrigation area gate in the current irrigation area traversal irrigation stage, and obtains the current traversal initial moment adjustable state parameter matrix, the current traversal irrigation stage unadjustable state parameter change equation matrix and the current traversal irrigation stage gate initial opening parameter set; The current traversal stage end gate opening parameter cyclic adjustment module cycles each current irrigation area traversal irrigation stage, and adjusts the opening parameters of each gate at the end time of each current irrigation area traversal irrigation stage by setting the ideal value of each type of adjustable state parameter data corresponding to each gate at the end time of each current irrigation area traversal irrigation stage, so as to obtain the final opening parameter matrix of the current irrigation gate.

[0023] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0024] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. An intelligent control method for integrated gates for irrigation area measurement and control, characterized in that: The following steps are involved: S1. Setting several types of state parameter types that can reflect the irrigation area to obtain an irrigation area state parameter type set; S2. Collect various types of adjustable state parameter data, gate opening parameters and various types of non-adjustable state parameter data of each gate in the current controlled irrigation area within multiple historical periods in the control decision interval in cooperation with the irrigation area state parameter type set to construct a final gate state parameter mapping equation matrix set; S3, collecting adjustable state parameter data, unadjustable state parameter change equations and gate opening parameters of each type of gates in the current irrigation area during the irrigation stage of the current irrigation area; S4. Input the data collected in S3 into the final gate state parameter mapping equation matrix for centralized mapping and loop through each current irrigation district through the irrigation stage. By setting the ideal value of each type of adjustable state parameter data corresponding to each gate at the end time of each current irrigation district through the irrigation stage, the opening parameters of each gate in each current irrigation district through the irrigation stage are adjusted to obtain the final opening parameter matrix of the current irrigation gate.

2. The intelligent control method for integrated gate control in irrigation area according to claim 1 is characterized in that: The S1 comprises the following steps: S11, setting several types of adjustable state parameter types and non-adjustable state parameter types that can reflect the irrigation area, the irrigation area gates, and the surrounding environment of the irrigation area, and obtaining a first irrigation gate state parameter type set and a second irrigation gate state parameter type set; setting the current irrigation area to be controlled, obtaining each gate in the current irrigation area to be controlled, and obtaining the current irrigation area gate set; S12. According to the current irrigation area to be controlled and the gate set of the current irrigation area, the gate control decision interval and the irrigation cycle of the current irrigation area are set.

3. The intelligent control method for integrated gate control in irrigation area according to claim 2 is characterized in that: The S2 comprises the following steps: S21, in conjunction with the irrigation area state parameter type set, the gate control decision interval, the current irrigation area irrigation cycle, the first irrigation gate state parameter type set and the second irrigation gate state parameter type set, collect various types of adjustable state parameter data corresponding to the initial and end times of the control decision interval for each gate in the current irrigation area to be controlled within multiple groups of historical cycles, the gate opening parameters and the change equations of various types of non-adjustable state parameter data between the initial and end times, and obtain the first current historical state parameter matrix, the second current historical state parameter matrix and the current historical gate opening parameter matrix; S22. Use the first current historical state parameter matrix, the second current historical state parameter matrix and the current historical gate opening parameter matrix to construct mapping equations for various types of adjustable state parameters corresponding to each gate in the current irrigation district gate set, and obtain a final gate state parameter mapping equation matrix set.

4. The intelligent control method for integrated gate control in irrigation area according to claim 3 is characterized in that: The S22 comprises the following steps: S221, constructing initial mapping equations of various types of adjustable state parameters corresponding to each gate in the current irrigation district gate set in conjunction with the first current historical state parameter matrix, the second current historical state parameter matrix, and the current historical gate opening parameter matrix, to obtain an initial gate state parameter mapping equation matrix set; S222, substitute the various types of adjustable state parameters at the initial moment of each gate control decision interval in the first current historical state parameter matrix, the change equations of various types of non-adjustable state parameter data within each gate control decision interval in the second current historical state parameter matrix, and the gate opening parameters at the initial moment and the end moment of each gate control decision interval in the current historical gate opening parameter matrix into the initial gate state parameter mapping equation corresponding to the initial gate state parameter mapping equation matrix set for mapping, and obtain the historical moment adjustable state parameter mapping data matrix; Calculate the error between the adjustable state parameter mapping data matrix at the historical moment and the adjustable state parameter at the end of each gate control decision interval corresponding to each gate in the first current historical state parameter matrix to obtain the current historical state parameter initial mapping error data matrix set; S223, setting the gate control decision interval state parameter mapping error threshold; adjusting the initial gate state parameter mapping equation matrix set according to the gate control decision interval state parameter mapping error threshold and the current historical state parameter initial mapping error data matrix set to obtain the final gate state parameter mapping equation matrix set.

5. The intelligent control method for integrated gate control in irrigation area according to claim 4 is characterized in that: In S223, the Mustang optimization algorithm is used to adjust the initial gate state parameter mapping equation matrix set.

6. The intelligent control method for integrated gate control in irrigation area according to claim 5 is characterized in that: The S3 comprises the following steps: S31, using the gate control decision interval to divide the current irrigation area irrigation cycle into stages to obtain a current irrigation area irrigation stage set; traversing the current irrigation area irrigation stage set and recording the current traversed current irrigation area irrigation stage as the current irrigation area traversed irrigation stage; In conjunction with the first flooding gate state parameter type set, the current irrigation area gate set and the second flooding gate state parameter type set, the adjustable state parameter data and the change equations of the non-adjustable state parameter data of each type of the current irrigation area gate corresponding to the initial moment of the current irrigation area traversal irrigation stage are collected to obtain the current traversal initial moment adjustable state parameter matrix and the current traversal irrigation stage non-adjustable state parameter change equation matrix; S32, collecting the opening parameters of each current irrigation district gate corresponding to the initial moment of the current irrigation district traversal irrigation stage, and presetting the opening parameters of each current irrigation district gate corresponding to the end moment of the current irrigation district traversal irrigation stage, to obtain the initial opening parameter set of the gate in the current traversal irrigation stage.

7. The intelligent control method for integrated gate control in irrigation area according to claim 6 is characterized in that: The S4 comprises the following steps: S41, inputting the adjustable state parameter matrix of the current traversal initial moment, the non-adjustable state parameter change equation matrix of the current traversal filling stage, and the initial gate opening parameter set of the current traversal filling stage into the corresponding mapping equation in the final gate state parameter mapping equation matrix set for mapping, to obtain the adjustable state parameter matrix of the current traversal final moment; S42, setting the ideal data corresponding to each type of adjustable state parameter data at the end of the irrigation stage of the current irrigation area, and obtaining the ideal value set of the adjustable state parameters at the end of the current stage; Adjust the initial opening parameter of each current irrigation area gate in the initial opening parameter set of the gate in the current traversal irrigation stage in conjunction with the ideal value set of the adjustable final state parameters in the current stage to obtain the final opening parameter set of the gate in the current traversal irrigation stage; S43, after the adjustment is completed, the next stage of the current irrigation area traversal irrigation stage is used as the current irrigation area traversal irrigation stage, and the final gate opening parameter set of the current irrigation area traversal irrigation stage is used as the opening parameter of each current irrigation area gate corresponding to the initial moment of the current irrigation area traversal irrigation stage; S31, S32, S41, S42 and S43 are repeated until the current irrigation area traversal irrigation stage is the last current irrigation area irrigation stage in the current irrigation area irrigation stage set; The final gate opening parameter set of the current traversal water filling stage obtained in each round of traversal is integrated to obtain the final opening parameter matrix of the current water filling gate; S44. In conjunction with the final opening parameter matrix of the current irrigation gate, the opening parameter of each gate corresponding to the irrigation of the current irrigation area to be controlled is set.

8. The intelligent control method for integrated gates for irrigation area measurement and control according to claim 7 is characterized in that: In S42, adjusting the initial opening parameter of each current irrigation area gate in the current traversal irrigation stage gate initial opening parameter set in conjunction with the current stage adjustable final state parameter ideal value set includes the following steps: S421, constructing a wild horse population for adjusting the gate opening parameters at the end of the current traversal stage; setting the maximum number of iterations of the wild horse population for adjusting the gate opening parameters at the end of the current traversal stage to And the current number of iterations is , respectively recorded as the maximum number of iterations for parameter adjustment and the current number of iterations for parameter adjustment; S422, setting the gate opening parameter at the end of the current traversal stage to adjust the initial position of each wild horse in the wild horse population, and obtaining a second initial position matrix; S423, constructing a fitness function for adjusting the wild horse population by using the gate opening parameter at the end of the current traversal stage; S424, start iteration; in each round of iteration, use the fitness function of the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage to calculate the fitness value of the position of each wild horse in the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage updated in the previous round of iteration, and update the position of each wild horse in the wild horse population adjusted by the gate opening parameter at the end of the current traversal stage updated in the previous round of iteration; S425, when When , stop the iteration and get the second final global optimal position; otherwise, continue to iterate until The second final global optimal position is used as the final gate opening parameter set of the current traversal irrigation stage.

9. A system for implementing the intelligent control method of an irrigation district integrated measurement and control gate as described in any one of claims 1 to 8.

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