immune-gengtic-simulation

代码说明：

说明：  为了更好了解遗传神经网络在系统中的对比效果，我们以室内温度控制为例，设室内的温度控制目标为18℃（20℃），其他参数保持不变的情况下，分别按照单独神经网络和基于遗传算法优化后的神经网络控制进行仿真实验.仿真结果表明，上述应用遗传算法优化的神经网络是非常有效的，通过运用遗传算法对神经网络进行优化，使其具有良好的泛化能力和快速的收敛性。(To better understand the genetic neural network contrast in the system, we control the indoor temperature, for example, set the room temperature control goal is 18 ℃ (20 ℃), other parameters remaining unchanged, respectively, according to a separate neural networks optimized based on genetic algorithm and neural network control simulation. The simulation results show that the genetic algorithm to optimize the neural network is very effective, through the use of genetic algorithms to optimize the neural network, it has a good generalization ability and fast convergence.)

文件列表：

immune gengtic simulation.doc,86016,2011-03-18