使用小波熵法对电力负荷时间序列进行预测。

企业数字神经网络功能开发文章，能进行BP等神经网络的设计-enterprise digital neural network function development articles, BP will carry out other neural network design

将遗传算法与蚁群算法相相结合，产生的一种新算法-genetic algorithm and ant algorithm combination of a new algorithm

这是我写毕业论文的源程序,用模拟退火算法求解VRPTW问题.在我机子上运行过了,结果很好.-This is the thesis I wrote the source code, using simulated annealing algorithm to solve VRPTW problems. In my machine run-off, resulting in very good.

遗传算法解H病态方程组-Genetic Algorithm for CSM Group H

朴素贝叶斯分类器（Navie Bayesian Classifier）识别鼠标输入的字母A～J-Naive Bayesian classifier (Navie Bayesian Classifier) Identification of the mouse input letters A-J

采用的是康力山等人确定的实验参数。 对于n个城市的旅行商问题，其参数如下： 初始温度：t0=280, 每一个温度下采用固定的迭代次数L=100n, 温度的衰减系数alpha=0.92 算法停止的准则是当相邻两个温度得到的解变化很小时算法停止。-used the Stanozolol Hill were determined by the experimental parameters. N cities for the traveling salesman problem, the parameters are as follows : initial temperature : t0 = 280, each a fixed temperature of the iteration number L = 100n, temperature attenuation coefficient alpha = 0.92 algorithm to stop the criteria when two adjacent the temperature change was very Solution Algorithm stop.

以某区水文数据为例，在matlab7中构建BP神经网络，进行仿真预测。-Hydrological data in a certain district, for example, in matlab7 Building BP neural networks, simulation prediction.

基于信息熵的免疫算法是一种修正的免疫算法，方法并不复杂，对于特定问题效果较好-Entropy-based immune algorithm is a modified immune algorithm, methods are not complicated, for the specific problem better

此文档是遗传算法原理加源代码。 生物的进化是一个奇妙的优化过程，它通过选择淘汰，突然变异，基因遗传等规律产生适应环境变化的优良物种。遗传算法是根据生物进化思想而启发得出的一种全局优化算法。 -This document is the principle of genetic algorithm source code increases. Biological evolution is a wonderful optimization process, it eliminated by choosing a sudden variation of genetic and other changes in the law to adapt to the environment arising from the fine species. Genetic algorithm is based on ideas of biological evolution and the inspiration derived from a global optimization algorithm.

该算法采用另外一种策略，结合进化策略和遗传算法，达到优化的目地-The algorithm uses a different strategy, combining evolutionary strategy and genetic algorithm to optimize the purpose