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Canal system water distribution optimization method based on double-layer particle swarm optimization algorithm

A technology of particle swarm algorithm and optimization method, which is applied in computing, instrumentation, data processing applications, etc., can solve problems such as long computing time, instability, and complex genetic algorithm design, and achieves improved computing efficiency, fast solution speed, and reduced water allocation. the effect of time

Active Publication Date: 2017-09-01
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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Problems solved by technology

[0015] The purpose of the present invention is to solve the complexity of the genetic algorithm design in the canal system optimization water distribution model when the existing lower canal system flow is not equal. When a large number of individuals are involved, it needs a long calculation time; Control parameters such as the selection method, convergence data, and hybridization mutation method need to be determined empirically, and premature convergence may occur, so that it may not always obtain the global optimal solution; multiple operations are required, and the solution cannot be obtained stably. An optimization method for canal water distribution based on double-layer particle swarm optimization

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  • Canal system water distribution optimization method based on double-layer particle swarm optimization algorithm
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  • Canal system water distribution optimization method based on double-layer particle swarm optimization algorithm

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specific Embodiment approach 1

[0041] Specific implementation mode one: combine figure 1 , figure 2 Describe this embodiment, the specific process of a kind of canal system water distribution optimization method based on double-layer particle swarm optimization algorithm in this embodiment is:

[0042] Step 1. Initialize the parameters of the Bi-PSO algorithm, and randomly generate the position X of the initial solution particle that satisfies the underlying constraints i And the model of velocity Vi, the position Y of the initial solution particle that satisfies the top-level constraints j and the model of velocity Vj; the specific process is:

[0043] The Bi-PSO algorithm is a two-layer particle swarm algorithm;

[0044] The double-layer particle swarm optimization algorithm consists of two layers, called the top layer and the bottom layer, respectively, the top layer is the canal system layer, and the bottom layer is the flow layer;

[0045] The parameters of the Bi-PSO algorithm include the particl...

specific Embodiment approach 2

[0075] Specific embodiment two: the difference between this embodiment and specific embodiment one is: the calculation of F(X in the step two i ,Y j ), as the first iteration of the initial particle, the individual optimal position is the particle itself, compare the fitness value of the particle, and use the particle with the optimal fitness value corresponding to each layer as the bottom layer, The top-level initial global optimal position particle; the specific process is:

[0076] F(X i ,Y j )’s initial target fitness function value includes objective function 1 and objective function 2, F is the fitness function, and the fitness function is the joint action of objective function 1 and objective function 2, and the fitness function is obtained by adding weights to the objective function reciprocal;

[0077] Objective function 1:

[0078]

[0079] In the formula, Z is the total water loss, V su , V sd Respectively, the total water loss of the upper and lower chann...

specific Embodiment approach 3

[0101] Embodiment 3: The difference between this embodiment and Embodiment 1 or 2 is that in the step 3, the bottom layer and the top layer are interactively iterated, and the method of synchronous optimization is used to update the speed and position of the initial solution particles; the specific process for:

[0102] The global optimal particle refers to the optimal particle among all the particles in each layer, and the individual optimal particle refers to the optimal particle when the position of each particle is constantly changing in each iteration, and the particle is changing, so Individual optimal particles are not better than global optimal particles;

[0103] The initialized particle, the initial particle has not been calculated, and does not know what the individual optimal particle is, so it regards itself as the individual optimal particle;

[0104] During each iteration, the particles in the drainage layer or flow layer update their positions by tracking two ...

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Abstract

The invention discloses a canal system water distribution optimization method based on a double-layer particle swarm optimization algorithm, so as to solve the problems that the genetic algorithm is complicatedly designed in a canal system optimization water distribution model when flows of the existing lower-level canal system are not equal, when a large amount of individuals are involved, a long calculation time is needed, control parameters such as a solvable group scale, a selection mode, convergence data and a hybridization variation mode of the genetic algorithm are determined by experience, premature convergence happens possibly, the global optimal solution can not be acquired constantly, multiple times of calculation are needed, and the solution can not be obtained stably. X, Vi, Y<j> and Vj are generated randomly; global optimal position particles at the bottom layer and the top layer are solved; updating on the speed and the position of an initial solution particle is carried out; whether to meet constraints is judged; the global optimal solution is obtained; and the optimal solution of the double-layer particle swarm optimization algorithm is obtained. The method of the invention is used for the canal system water distribution field.

Description

technical field [0001] The invention relates to a canal system water distribution optimization method based on a double-layer particle swarm algorithm. Background technique [0002] The optimal water distribution of the canal system refers to the optimization of the rotation irrigation combination of the water distribution channel by adopting certain methods and technologies in order to meet the irrigation requirements of crops in the irrigation area under the condition of certain water flow capacity of the water distribution channel and its subordinate channels. As an important research direction in the field of optimal allocation of water resources, scientific and rational decision-making for optimal water allocation in canal systems can reduce seepage loss and waste water in the process of water delivery in canal systems, which is of great significance for improving water use efficiency and grain production. Due to the differences in topography, external conditions and th...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 刘照张树清李华朋丁小辉魏延生
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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