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this is an e-book about Training Feedforward Neural Networks Using Genetic Algorithms
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针对传统的ＢＰ或ＧＡ对模糊神经网络的识别应用存在收敛容易陷入局部极小 识别率低下等问题 提出一
种基于ＢＦＧＳ的混合遗传算法 其基本思想为 首先构造一种前馈型模糊神经网络结构 然后用遗传算法进化若干代
后 当目标函数的梯度或者范数小于预先设定值 则改用ＢＦＧＳ算法进行优化识别 仿真实验表明 对比ＧＡ该算法
收敛速度较快 识别精度提高了约７％ 能够较好地应用于一类模糊神经网络的识别-In traditional BP or GA to identify the application
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Design a feedforward network is u
dehaze algorithms review
path planning using GA and ACO...
The neural network adaboost stron
TS neural network m files, fast c
bp neural network, written with C
Bayes net and memory based learni
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1下载：
Design a feedforward network is u
dehaze algorithms review
path planning using GA and ACO...
The neural network adaboost stron
TS neural network m files, fast c
bp neural network, written with C
Bayes net and memory based learni
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This framework implements a agent-based model simulating the speciation of biological agents in an environment, analyzing their evolution of a sense of time, i.e. a behavior sensitive to schedules, cycle repetitions and memory effects. The agents use
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使用遗传算法优化BP神经网络的权值和阈值。BP神经网络是一种按照误差逆向传播算法训练的多层前馈神经网络，是应用最广泛的神经网络。(Genetic algorithm is used to optimize the weights and thresholds of BP neural network. BP neural network is a kind of multilayer feedforward neural network trained according to the erro
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