SVM ppt from Peking Univ., it may be useful to the learners or researchers who a...

该程序是基于BP网络的PID控制系统。系统由两部分构成：经典的PID控制器和神经网络。-that the procedure was based on BP network PID control system. System consists of two parts : the classic PID controller and neural networks.

研究基于遗传编程的可持续性进化算法的理论与方法，并建立了该算法的数学模型及运算流程.HFC算法实现源代码.-Research based on genetic programming evolutionary algorithm for the sustainability of the theory and method, and set up a mathematical model of the algorithm and the computation flow. HFC algorithm source code implementation.

这是一个的遗传算法程序,开发平台是vc7.0-This is a genetic algorithm process, the development platform is vc7.0

利用hopfield神经网络解决TSP(旅行商)问题-use hopfield neural network to solve TSP salesman problem (TSP)

这还是一个蚁群算法实验室,不过内容要更为详细,看得更为清楚,可以用它来理解蚁群的整个觅食过程.-It is also a laboratory ant colony algorithm, but the content should be more detailed, more clearly seen, you can use it to understand the whole feeding process of ant colony.

使用clips解决4人限定时间过河问题。附带clips源代码。-use clips resolve four limit the time the river issues. Fringe clips source code.

路由选择过程的c算法程序 与DSR 只是简单地使用最短路径不同，EMRPC 使用了更复杂的路由选择机制以实现多径路由和能量均衡。-process of routing algorithm c procedures and DSR is simply to use the shortest path different. EMRPC use of a more complex routing mechanisms to achieve multi-path routing and energy balance.

用模拟退火算法求解TSP问题-simulated annealing algorithm for TSP

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,

神经网络理论与Matlab7电子工业出版社原代码-neural network theory and Matlab7 Electronic Industry Publishing House source