遗传算法,实现的是一个猜答案的过程， 这种算法比较经典，可以借鉴...

朴素贝叶斯分类器（Navie Bayesian Classifier）识别鼠标输入的字母A～J-Naive Bayesian classifier (Navie Bayesian Classifier) Identification of the mouse input letters A-J

neural network in Java

实数编码 遗传算法 C++用matlab实现实数编码 遗传算法 C++用matlab实现-Real-coded genetic algorithm C++ Using matlab realize real-coded genetic algorithm C++ Realize using matlab

一个遗传算法源程序 可以作为学习改进使用 希望对大家有所帮助-A genetic algorithm source code can be used as learning to improve the use of want to be helpful to everyone

高手学习人工智能心得体会。想学习人工智能的可以来-master learning artificial intelligence experiences. Want to study artificial intelligence can s

清华大学对robocup中kick的研究源码-Tsinghua University s study robocup source of kick

一种通过自组织竞争学习网络实现数据降维和可视化的单层神经网络模型。用此算法可以把输入空间的多维映射到低维的（一维或者二维）的离散网络上，并将保持相同性质的输入数据在映射到低维空间时的拓扑一致性。iris以及letter两个数据集进行分类-A competitive learning through self-organizing network for data dimensionality reduction and visualization of single-layer neural network model. Using this algorithm can be multi-dimensional input space is mapped to the low-dimensional (one-dimensional or two-dimensional) discrete network, and will remain the same as the nature of the input data is mapped to the low-dimensional space of topological consistency. iris as well as the letter the two data sets to classify

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.

This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL

同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-comparison with the genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications