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 Description: MATLAB code The first chapter is BP neural network data classification -- speech characteristic signal classification The second chapter is the nonlinear system modeling of BP neural network nonlinear function fitting The third chapter, genetic algorithm optimization BP neural network - nonlinear function fitting The fourth chapter, neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking The fifth chapter is based on BP_Adaboost's strong classifier design -- the company financial early-warning model The sixth chapter is PID neural network decoupling control algorithm multivariable system control The seventh chapter is the regression of RBF network the realization of nonlinear function regression .........the last is 58 chapters
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代码

代码\44层次分析

代码\44层次分析\CENCI2.m

代码\45灰色关联度度

代码\45灰色关联度度\huiseguanliand1.m

代码\46熵权法

代码\46熵权法\sqf.m

代码\47主成分分析

代码\47主成分分析\pca.m

代码\48主成分回归

代码\48主成分回归\PCR_Demo.m

代码\49偏最小二乘回归

代码\49偏最小二乘回归\PLS.m

代码\50逐步回归

代码\50逐步回归\stepwise.zip

代码\51模拟退火

代码\51模拟退火\SA_GUI_Demo

代码\51模拟退火\SA_GUI_Demo\fitness.m

代码\51模拟退火\SA_GUI_Demo\html

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo.html

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo.png

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_01.png

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_02.png

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_03.png

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_04.png

代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_05.png

代码\51模拟退火\SA_GUI_Demo\main.m

代码\51模拟退火\SA_TSP_Demo

代码\51模拟退火\SA_TSP_Demo\Distance.m

代码\51模拟退火\SA_TSP_Demo\DrawPath.m

代码\51模拟退火\SA_TSP_Demo\Metropolis.m

代码\51模拟退火\SA_TSP_Demo\NewAnswer.m

代码\51模拟退火\SA_TSP_Demo\OutputPath.m

代码\51模拟退火\SA_TSP_Demo\PathLength.m

代码\51模拟退火\SA_TSP_Demo\html

代码\51模拟退火\SA_TSP_Demo\html\main.html

代码\51模拟退火\SA_TSP_Demo\html\main.png

代码\51模拟退火\SA_TSP_Demo\html\main_01.png

代码\51模拟退火\SA_TSP_Demo\html\main_02.png

代码\51模拟退火\SA_TSP_Demo\html\main_03.png

代码\51模拟退火\SA_TSP_Demo\main.m

代码\52RBFGRNNPNN-神经网络

代码\52RBFGRNNPNN-神经网络\ClassCode

代码\52RBFGRNNPNN-神经网络\ClassCode\html

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_GRNN_PNN.html

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_GRNN_PNN.png

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_GRNN_PNN_01.png

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_GRNN_PNN_02.png

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_GRNN_PNN_03.png

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_RBF.html

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_RBF.png

代码\52RBFGRNNPNN-神经网络\ClassCode\html\main_RBF_01.png

代码\52RBFGRNNPNN-神经网络\ClassCode\iris_data.mat

代码\52RBFGRNNPNN-神经网络\ClassCode\main_GRNN_PNN.m

代码\52RBFGRNNPNN-神经网络\ClassCode\main_RBF.m

代码\52RBFGRNNPNN-神经网络\ClassCode\spectra_data.mat

代码\53 竞争神经网络与SOM神经网络

代码\53 竞争神经网络与SOM神经网络\ClassCode.rar

代码\54蚁群算法tsp求解

代码\54蚁群算法tsp求解\citys_data.mat

代码\54蚁群算法tsp求解\html

代码\54蚁群算法tsp求解\html\main.html

代码\54蚁群算法tsp求解\html\main.png

代码\54蚁群算法tsp求解\html\main_01.png

代码\54蚁群算法tsp求解\html\main_02.png

代码\54蚁群算法tsp求解\main.m

代码\55灰色预测

代码\55灰色预测\gm1_1benrentest.m

代码\56 模糊综合评价

代码\56 模糊综合评价\27194323mohu.rar

代码\58曲线拟合

代码\58曲线拟合\myfun.m

代码\58曲线拟合\nihe.m

代码\58曲线拟合\拟合图.png

代码\chapter1

代码\chapter1\BPDLX.m

代码\chapter1\chapter1_1.asv

代码\chapter1\chapter1_1.m

代码\chapter1\data1.mat

代码\chapter1\data2.mat

代码\chapter1\data3.mat

代码\chapter1\data4.mat

代码\chapter10

代码\chapter10\Readme.txt

代码\chapter10\chapter10.m

代码\chapter10\class.mat

代码\chapter10\sim.mat

代码\chapter10\stdlib.m

代码\chapter10\test.m

代码\chapter11

代码\chapter11\Readme.txt

代码\chapter11\city_location.mat

代码\chapter11\diff_u.m

代码\chapter11\energy.m

代码\chapter11\main.m

代码\chapter12

代码\chapter12\Chapter_ClassifyRegressUsingLibsvm.m

代码\chapter12\heart_scale.mat

代码\chapter12\html

代码\chapter12\html\Chapter_ClassifyRegressUsingLibsvm.html

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