人工智能bp算法程序以及实验报告

这个程序对快速实现模糊逻辑控制很有用。假设这个逻辑控制有两个输入和一个输出，用各种选择来实现它。-This procedure is the rapid realization of the usefulness of fuzzy logic control. Assuming that there are two logic control inputs and one output, with various options to achieve it.

改进的BP算法程序,希望对大家有所帮助.如果需要，请-The BP algorithm to improve the process, everyone would like to help. If necessary, please take a look at.

仿真1：首先把网络温度参数T固定在100，按工作规则共进行1000次状态更新,把这1000次状态转移中网络中的各个状态出现的次数Si（i＝1，2，…，16）记录下来 按下式计算各个状态出现的实际频率： Pi=Si/∑i=1,NSi=Si/M 同时按照Bo1tzmann分布计算网络各个状态出现概率的理论值： Q（Ei）=（1/Z）exp（-Ei/T） 仿真2：实施降温方案，重新计算 采用快速降温方案：T（t）= T0/（1+t） T从1000降到0.01，按工作规则更新网络状态 当T=0.01时结束降温，再让T保持在0.01进行1000次状态转移，比较两种概率-a simulation : First of all network parameters temperature T fixed at 100 and, according to the rules for a total of 1000 to update the state, this state of the 1000 network transfer of all states for the number of Si (i = 1, 2, ..., 16) all recorded determined by the formula state-of the actual frequency : Pi = Si/i = 1, NSi = Si/M in accordance with Bo1tzmann distributed computing network of states all probability the theoretical value : Q (Ei) = (1/Z) exp (- Ei/T) Simulation 2 : implementation of cooling, re-using rapid cooling programs : T (t) = T0/(1 t) T dropped to 0.01 from 1000 and, according to the rules updated network state when T = 0.01 at the end of cooling, let T at 0.01 for the 1000 state tran

用人工神经网络实现格林码的编码，通过对网络的训练实现，输入一串0/1码得到其格林码-using artificial neural networks Green codes, the network through training, input string of 0/1 yards code to be its Green

基于遗传算法的模糊卡尔曼滤波器-Fuzzy kalman filter based on inheritance algorithmic.

讲述关联规则在零售业中的作用,相应的算法和实例实现-on association rules in the retail sector"s role, the corresponding algorithm to achieve and examples, etc.

ART2自组织神经网络vc++源程序，调试通过，可以使用。-ART2 self-organizing neural network vc++ Source code, debugging through, you can use.

这是一篇美国博士毕业设计的论文，是用神经网络实现mppt的方案-This is a graduation project of the United States, Dr. thesis, is to use neural network program to achieve MPPT

CPN能提供强大的分类功能.介绍CPN(Counter Propagation Networks)神经网络的结构、训练及计算的基础上,详细讨论了CPN在离散事件动态系统(DEDS)仿真、仿真优化等方面的应用。 -CPN can provide powerful classification. Introduction CPN (Counter Propagation Networks) neural network structure, training and calculated on the basis of a detailed discussion of the CPN in Discrete Event Dynamic System (DEDS) simulation, simulation optimization applications.

VC中利用人工智能解决八迷宫问题。这是一个很有趣的人工智能小程序，不妨试试看。-use artificial intelligence to solve eight problems maze. This is a very interesting small artificial intelligence procedures, it may try.