文件名称:psoToolbox
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失败请重下，重下不扣分。
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Help psoToolbox V1.0
psoToolbox provides an interective GUI based Toolbox to solve
optimization problems using particle swarm optimization.
Creat a fitness function in M-file.
Inputs:
Function : Function handle of fitness function.
Nvars : Number of variable to be optimized.
LB : Lower Bound of Nvars (1 X Nvars)
UB : Upper Bound of Nvars (1 X Nvars)
Parameters:
C1 : Cognative Attraction
C2 : Social Attraction
W : Inertial
Population Size : Number of Swarms
Max Iterations : Maximum number of epochs.
Click on " RUN PSO " button to start PSO search. You will get the out put
at Edit box below the axes.-Help psoToolbox V1.0
psoToolbox provides an interective GUI based Toolbox to solve
optimization problems using particle swarm optimization.
Creat a fitness function in M-file.
Inputs:
Function : Function handle of fitness function.
Nvars : Number of variable to be optimized.
LB : Lower Bound of Nvars (1 X Nvars)
UB : Upper Bound of Nvars (1 X Nvars)
Parameters:
C1 : Cognative Attraction
C2 : Social Attraction
W : Inertial
Population Size : Number of Swarms
Max Iterations : Maximum number of epochs.
Click on " RUN PSO " button to start PSO search. You will get the out put
at Edit box below the axes.
psoToolbox provides an interective GUI based Toolbox to solve
optimization problems using particle swarm optimization.
Creat a fitness function in M-file.
Inputs:
Function : Function handle of fitness function.
Nvars : Number of variable to be optimized.
LB : Lower Bound of Nvars (1 X Nvars)
UB : Upper Bound of Nvars (1 X Nvars)
Parameters:
C1 : Cognative Attraction
C2 : Social Attraction
W : Inertial
Population Size : Number of Swarms
Max Iterations : Maximum number of epochs.
Click on " RUN PSO " button to start PSO search. You will get the out put
at Edit box below the axes.-Help psoToolbox V1.0
psoToolbox provides an interective GUI based Toolbox to solve
optimization problems using particle swarm optimization.
Creat a fitness function in M-file.
Inputs:
Function : Function handle of fitness function.
Nvars : Number of variable to be optimized.
LB : Lower Bound of Nvars (1 X Nvars)
UB : Upper Bound of Nvars (1 X Nvars)
Parameters:
C1 : Cognative Attraction
C2 : Social Attraction
W : Inertial
Population Size : Number of Swarms
Max Iterations : Maximum number of epochs.
Click on " RUN PSO " button to start PSO search. You will get the out put
at Edit box below the axes.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
findsqrt.m
license.txt
pso.m
psoToolbox.m
psoToolbox.mlappinstall
screen.png