神经网络训练算法,很快 很简单 很适用 能快速用到实验环境中去...

matlab小程序，为初学者提供一些常用的例子-There provide some basic matlab programs that will help a biginer a lot.

人工智能课程中关于产生式系统部分上机实验的源代码，有很大参考价值。-No

这是通过A*算法实现8数码问题，求解可能出现的目标状态。通过回溯的方法实现对A*算法。不同于其它状态图的搜索实现8数码问题。-This is the A* algorithm eight digital issues, the solution may target state. Through the method back to the A* algorithm. Unlike other state diagram of the search to achieve eight digital problem.

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

收集的关于遗传算法的模糊搜索的ppt资料，有兴趣的可以研究一下-Collected on the genetic algorithm ppt fuzzy search information, interested can look at

Genetic Algorithm (GA) based solver for the Traveling Salesman Problem

兔子狐狸生态平衡模拟器，可以模拟兔子狐狸相互依存的状况。-The zoology balance simulator of rabbit and fox ,which can simulate the status of rabbit and fox depended on each other.

数据挖掘中的ID3算法源码 决策树的经典算法之一。 -Data Mining Source ID3 decision tree algorithm, one of the classic algorithm.

TSP问题是组合优化中的经典问题。其解决方法有局部优化方法和一些启发式算法,局部搜索方法充分考虑问题 的邻域结构,遗传算法有很好的全局搜索能力,memetic算法把遗传算法和局部优化算法相结合,试验结果证明,能很好地解 决TSP问题。-TSP problem is a classic combinatorial optimization problem. Its solution has a number of local optimization methods and heuristic algorithms, local search methods take full account of the issue of neighborhood structure, genetic algorithm has good ability of global search, memetic algorithm for the genetic algorithm and local optimization algorithm combining test results proved that well positioned to solve the TSP problem.

matlab程序计算经典数学问题：最短路和次短路问题-matlab program calculated the classical mathematical problem: The most short-circuit and sub-shortest path problem