自适应遗传算法，采用C编写，比较适应开始学习遗传算法的人学习...

C 语言编缉神经网络工具-neural network tools edited by C language

JESS开发模式，人工智能开发架构-JESS development model, the development of artificial intelligence structure

一个*算法，有详细的描述过程，其中的奥秘自己看。

目前最好的A*寻路算法-Currently the best A* pathfinding algorithm. . . . . . . . .

离散数学中---------一阶谓词演算源代码-Discrete Mathematics- First order predicate calculus source code

本文在学习探讨VSM算法的同时，对SVM在液压系统故障诊断中的应用进行了论述。以液压设备中常见的克令吊为研究对象，运用支持向量机理论对其进行故障诊断的仿真研究和实验研究，其中包括实验系统数学模型的设计、仿真模型的建立(用SIMUL工NK仿真软件建立仿真模型)、特征参数的提取、数据的采集等。-In this paper, VSM learning algorithm to explore the same time, SVM in the hydraulic system fault diagnosis are discussed. With hydraulic equipment in the common crane as the research object, using support vector machine theory of their fault diagnosis simulation and experimental studies, including a mathematical model experimental system design, simulation model (using SIMUL Engineering Simulation NK Software to build simulation models), the extraction of characteristic parameters, data collection and so on.

用遗传算法优化神经网络权值的源程序-genetic algorithm optimization neural network value of the source

改进遗传算法在TSP中的应用!很好用哦!-Improved Genetic Algorithm in TSP application! Good use Oh!

文中设计了一个3层径向基神经网络(RBFN)用于对企业的5项评价指标进行聚类分析，并与蚁群算法做了比较分析。RBFN由输入层 到隐含层采用传统的K一均值算法，隐含层到输出层通过“模2递减”学习速率的BP学习；蚁群算法根据信息素的分配能够自动调整收索 路径，从而达到数据自动聚类的目的。结果表明，与蚁群算法相比，改进RBFN具有快速收敛、自动识别奇异样本的优点，而蚁群算法 无须教师学习，并能够达到全局最优。-In this paper, we designed a 3-layer RBF neural network (RBFN) for the 5-to-business evaluation indicators cluster analysis and ant colony algorithm has done a comparative analysis. RBFN from input layer to hidden layer using the traditional K-means algorithm, hidden layer to output layer through the Mode 2 decreasing learning rate of BP learning ant colony algorithm based on pheromone can automatically adjust the allocation of land Faso path, thereby to achieve the purpose of automatic data clustering. The results showed that compared with the ant colony algorithm to improve the RBFN has a fast convergence, automatic identification of singular advantage of the sample, while the ant colony algorithm do not need teachers to learn and be able to reach the global optimum.

< 神经网络设计源代码>>一书的源代码。-err