FNN利用MATLAB编程安装nefcon遵循这些步骤：1。打开…

模糊算法，实现了求交法计算模糊蕴含关系、最大最小法进行合成运算、求并法计算输出量的模糊集合、加权平均法计算实际的清晰控制量等部分的详细代码。-Fuzzy algorithm, the realization of the intersection method to calculate fuzzy implication relations, max-min method for synthesis of computing, and method for output fuzzy sets, the weighted average method to calculate the actual volume of clear control of part of the detailed code.

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

MATLAb语言的遗传算法工具箱，比较全。-MATLAb language of genetic algorithm toolbox, the entire comparison.

落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因素呈非线性关系。人工神经网络具有表示任意非线性关系和学习的能力,是解决复杂非线性、不确定性和时变性问题的新思想和新方法。基于此,作者提出自适应神经网络的落煤残存瓦斯量预测模型,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。结果表明,自适应调整权值的变步长BP神经网络模型预测精度高,收敛速度快 该预测模型的应用可为采掘工作面瓦斯涌出量的动态预测提供可靠的基础数据,为采掘工作面落煤残存瓦斯量的确定提出了一种全新的方法和思路。-charged residual coal gas is to determine the volume of mining gas emission rate forecast an important link, which directly affect mining gas emission rate forecast accuracy, and with coal metamorphism, loading coal particle size, the original gas content, exposure time and other factors nonlinear relationship. Artificial neural networks have expressed arbitrary nonlinear relationships and the ability to solve complex nonlinear, time-varying uncertainty and the new ideas and new approaches. Based on this, the author of adaptive neural network loading coal residual gas production forecast model, and a combination of different loading coal mine gas remnants of the actual test results of research

人工股市（Artificial Stock Market，简称ASM）是模拟股市运作的一个程序。在这个电脑中的虚拟市场中，若干被称为交易者的人工智能程序(Agent)通过观察它们所在的数字世界中股价和股息的不断变换而做出预测，并且根据这些预测做出购买股票与否以及购买股票数量的决策。反过来，所有的交易者的决策又决定了股票的价格，这样，整个的股票交易市场就构成了一个自我封闭的计算系统。同时，这些交易者都具有学习的能力，可以根据以前预测的成功或者失败对自己的决策进行调整，并且通过一种被称为遗传算法的方法产生创新能力。-artificial stock market (Artificial Stock Market, or ASM) is a stock market simulation operation of the procedure. In this computer in the virtual market, a number of traders known as artificial intelligence (Agent) by observing them where the digital world and the stock dividend and the constantly changing projections, and based on these projections made whether or not to purchase stocks and the purchase of shares in decision-making. Conversely, all the decision-making transactions in turn determines the share price, so that the entire stock market would constitute a self-enclosed computer system. Moreover, these transactions are capable of learning, can be predicted based on previous success or failure of their decisions for the

遗传算法的文章- Heredity algorithm article

基于遗传算法的人工生命模拟，C++源代码-Based on genetic algorithm artificial life simulation, C++ Source code

BP人工神经网络算法的实现，用java代码编写，案例是港口吞吐量预测。

这是目前网上所能找到的最全面的adaboost的C++算法，但是需要自己训练的数据-This is the Internet can find the most comprehensive adaboost C algorithms, However, it needs its own training data

清华大学不确定规划教材中的用遗传算法训练神经元网络的混合智能算法1-Tsinghua University, uncertainty in the planning of teaching materials by using genetic algorithm trained neural network Hybrid Intelligent Algorithm 1