A self-adaptive inertia weight chaotic particle swarm algorithm
A chaotic particle swarm, inertial weight technology, applied in computing, data processing applications, special data processing applications, etc., can solve the problems of stable system operation, complex algorithms, and many parameters to adjust, and achieves guaranteed diversity and search accuracy. High, reducing the effect of fluctuations
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[0018] An adaptive inertia weight chaotic particle swarm algorithm of the present invention is described below in conjunction with the accompanying drawings.
[0019] Please refer to figure 1 , an adaptive inertia weight chaotic particle swarm algorithm, including the following steps:
[0020] S1: Initialize the inertia weight ω 0 , acceleration factor c 1 、c 2 , population size N, maximum number of iterations N m , determine the search space [-x max , x max ] and the maximum velocity v max ;
[0021] In step S1, the velocity and position update equations of particle i are as follows:
[0022] v id (t+1)=ω·v id (t)+c 1 r 1 ·(p id (t)-x id (t))+c 2 r 2 ·(p gd (t)-x id (t)) (1)
[0023] x id (t+1)=x id (t)+v id (t+1) (2)
[0024] Among them, t is the number of particle update iterations. In generation t, the "best" position experienced by particle i in the d-dimensional space is recorded as The "best" particle position in the particle swarm is denoted a...
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