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Size: 807936 |
Author: guojingiing |
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Description: MATLAB神经网络30个案例分析__读者调用案例的时候，只要把案例中的数据换成自己需要处理的数据，即可实现自己想要的网络。该书共有30个MATLAB神经网络的案例(含可运行程序），包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络；还包含PSO(粒子群）、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。-30 case studies of the MATLAB Neural Network __ readers call the case, as long as the data in the case replaced by the data they need to be addressed, you can achieve your desired network. A total of 30 MATLAB neural network case (including running the program) in the book, including BP, RBF, SVM, the SOM, Hopfield, on LVQ, Elman, wavelet neural network also contains the PSO (Particle Swarm), gray neural network, fuzzy networks, probabilistic neural networks, genetic algorithms optimization.
Platform: |
Size: 11300864 |
Author: liuwei |
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Description: 共有30个MATLAB神经网络的案例(含可运行程序），包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络；还包含PSO(粒子群）、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。-Neural network cases
Platform: |
Size: 5555200 |
Author: 郑雪 |
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Description: pso优化svm的程序。C版。可以用于一些预测性问题-pso optimization svm
Platform: |
Size: 7168 |
Author: zwy |
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Description: 实现pso优化svm的程序。并有实验数据作了说明-Achieve pso to optimize the procedure of the svm. And experimental data gave an explanation
Platform: |
Size: 1024 |
Author: zhangjinhui |
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Description: 基于PSO训练SVM的人脸识别利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径 已通过测试。
-Good performance, performance in the ability to learn the use of support vector machines based on PSO training SVM face recognition combined kernel principal component analysis feature extraction method will be applied to the face recognition, the method in experiments demonstrated good recognition performance identify a new pathway for face recognition has been tested.
Platform: |
Size: 1098752 |
Author: wgh |
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Description: 利用PSO优化SVM中的c和g
c1:初始为1.5,pso参数局部搜索能力
c2:初始为1.7,pso参数全局搜索能力
maxgen:初始为200,最大进化数量
sizepop:初始为20,种群最大数量-Support Vector Machine Optimized by Particle Swarm Optimization
Platform: |
Size: 2048 |
Author: 蒋樟生 |
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Description: 本书共有30个MATLAB神经网络的案例,包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络,还包含PSO(粒子群)、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。-The book consists of 30 MATLAB neural network case (including program can be run), including BP, RBF, SVM, SOM, Hopfield, LVQ, Elman, wavelet neural networks, etc. also contains the PSO (PSO), gray neural networks, fuzzy networks, probabilistic neural networks, genetic algorithm optimization and so on.
Platform: |
Size: 28765184 |
Author: 万二 |
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Description: 利用遗传算法GA和粒子群算法PSO对SVM进行优化-GA genetic algorithm and particle swarm optimization PSO to optimize the SVM
Platform: |
Size: 285696 |
Author: caoji |
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Description: SVM用于分类时的参数优化，粒子群优化算法，用于优化核函数的c,g两个参数-SVM PSO
Platform: |
Size: 4096 |
Author: 雨乔 |
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Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorithms in improving the classification accuracy of SVM for
condition assessment of power transformer.
Platform: |
Size: 985088 |
Author: pse |
Hits:
Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applic
Platform: |
Size: 1890304 |
Author: pse |
Hits:
Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorit
Platform: |
Size: 930816 |
Author: pse |
Hits:
Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorithms in improving the classification accuracy of SVM for
condition
Platform: |
Size: 670720 |
Author: pse |
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Description: 将SVM与粒子群算法(PSO)相结合,充分利用SVM在处理小样本回归问题上具有的独特优越性及PSO全局搜索优化等特点-SVM and particle swarm optimization algorithm (PSO) combined with SVM, makes full use of the unique superiority and the PSO global search optimization features in small sample regression problems on
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Size: 2048 |
Author: matlab |
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Description: Matlab使用pso进行svm参数优化寻优-Matlab were svm parameter optimization using pso optimization
Platform: |
Size: 2048 |
Author: matlab |
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Description: Matlab使用pso进行svm参数优化寻优-Matlab were svm parameter optimization using pso optimization
Platform: |
Size: 2048 |
Author: matlab |
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Description: pso算法在svm上的实践，有很强的应用价值，希望大伙会喜欢哦-Practice of PSO algorithm on SVM, it has strong application value, I hope everyone will like
Platform: |
Size: 221184 |
Author: 雷锋 |
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Description: Modified binary PSO for feature selection using SVM applied to
mortality prediction of septic patients
Platform: |
Size: 440320 |
Author: sangeetha |
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Description: 粒子群优化参数的LSSVM，并对啤酒数据进行分类-PSO LS SVM parameters, data classification and beer
Platform: |
Size: 10240 |
Author: 杨 |
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