Description: 遗传算法(GA)和神经网络(network)结合的算法,用于图像分类,包含完整的工程-Genetic Algorithm (GA) and neural network (network) combining algorithm, for image classification, including the complete works Platform: |
Size: 25600 |
Author:haoyubao |
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Description: 一本不错的介绍用遗传算法优化BP神经网络的书和程序-A good introduction to using genetic algorithm optimization BP neural network and procedures of the book Platform: |
Size: 11264 |
Author:王海波 |
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Description: 对于小样本而言,SVM的仿真效果要比神经网络好,但是SVM的性能依赖于它的两个训练参数,本算法是用GA自动选择SVM的两个参数。-For small sample case, SVM simulation results than the neural network is good, but the performance of SVM depends on its two training parameters, the algorithm is automatically selected GA parameters of SVM-2. Platform: |
Size: 1674240 |
Author:单志 |
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Description: 用遗传算法优化BP神经网络的初始权值与阈值.使用gaot与nntools-Use ga optimative the weight and bias of BP neural network. Platform: |
Size: 35840 |
Author:dynamicansys |
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Description: 基于遗传算法和小波神经网络的语音识别系统,此系统识别率可以到较高-Based on genetic algorithm and neural network speech recognition system, this system can be to a higher recognition rate Platform: |
Size: 314368 |
Author:斯芸芸 |
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Description: 主要是遗传神经网络运用于工业实践,欢迎大家参加借鉴,也欢迎交流与合作。-Genetic neural network is mainly used in industrial practice, welcome you to learn, exchange and cooperation are also welcome. Platform: |
Size: 4096 |
Author:zhoumin |
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Description: 用遗传算法来改善BP神经网络模型,可以很好的用于最优化、预测等问题的求解-Using genetic algorithms to improve the BP neural network model, can be very good for optimization, forecasting and other problem solving Platform: |
Size: 2048 |
Author:童康 |
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Description: 研究了两种全局优化算法:遗传算法( Genetic Algorithm , GA) 和模拟退火(Simulated Annealing ,SA) ,并且比较了它们在神经网络优化中的性能。-Study of two global optimization algorithms: genetic algorithm (Genetic Algorithm, GA) and simulated annealing (Simulated Annealing, SA), and compared them to the performance of neural network optimization. Platform: |
Size: 23552 |
Author:fy |
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Description: 用遗传算法优化BP神经网络的源程序代码 很好很强大-The source code of the BP neural network using genetic algorithm optimization is a very powerful Platform: |
Size: 56320 |
Author:lihongyan |
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