基于Hopfield神经网络解决旅行商问题，模式…

遗传算法的示例- Heredity algorithm demonstration

人工智能中九宫问题的实现，初始数据随机生成，最终状态随机生成，并用图形界面显示搜索过程-AI JiuGongTu the realization of the initial data randomly generated, the final state of random generation, and using a graphical interface shows search process

一个蚁群算法，大家很想要得东东，共享给大家了。-an ant colony algorithm, we want to fine Eastern, we had to share.

人工智能模式识别中基于支持向量机的分类算法在识别领域属于较新的应用-The SVM-based classification algorithm is a kind of new application in the field of artificial intelligence and pattern recognition.

遗传算法-理论和应用与软件实现，这是一本比较好的书-Genetic algorithms- theory and application and software implementation, this is a good book

内附两个源代码，其中一个源代码是识别程序的，另一个是一个矩阵类库的，所以一并附上。 ~..~因为已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。 当然读者也可以自行用训练样本训练网络，不过要特别注意训练样本的选择，否则可能造成识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下，训练样本数目尽量多。 -containing 2 source code, which is a source identification procedures, and the other is a matrix class library. So accompanied. ~ ~ .. Has been preserved because of the trained network weights, the first use of the identification procedures, can be run directly Release directory executable file, Then the catalog of tests conducted read into the picture, recognition. Certainly readers can use their own training samples training network, but special attention should be paid to the choice of training samples, Otherwise, it could cause a very low recognition rate. Training sample selection principle is that as far as possible be representative, in the training of the time not too long under the circumstances, the number of training samples as much as possible.

gasample遗传算法代码-gasample genetic algorithm code

对著名的UCI机器学习库的wine数据集做的朴素贝叶斯分类算法，包含详细源代码和实验报告，不可多得啊-Pairs of well-known UCI machine learning repository data set to do wine Naive Bayesian classification algorithm, with detailed source code and test reports, a rare ah

人工智能的8数码问题的求解-eight digital artificial intelligence problem solving

一款改进了的查询系统----北京公交车查询系统-new improved system for the Beijing-Bus Inquiry System