蚂蚁算法（或蚁群算法，ant colony algorithm）是由Colorni和Dorigo等人提出的一类模拟自然界蚁群行为的模拟进化算法。 这类算法主...

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

kmeans算法,许多同学做毕设需要用到-kmeans algorithm, many students needed to do to complete set up

经典的人工智能问题 - iris数据分析问题。通过设计三层bp神经网络对花朵数据进行分类识别，并达到了很好的效果。-classic AI problem- iris data analysis problems. Three-bp through the design of neural networks classify data flower identification, and to achieve good results.

神经网络中的感知机的学习算法的c语言程序源代码-neural network of Perceptron learning algorithm in C language source code

使用matlab应用遗传算法进行函数优化-Using genetic algorithm in matlab to optimize function

一个vc开发的支持向量机程序，对于初学者很有用．共享以下．-vc development of a support vector machine procedures, very useful for beginners. Sharing the following.

《游戏编程中的人工智能技术》一书中10，11章源代码- Game programming in artificial intelligence technology, one source book, Chapter 10,11

一个简单实用的K紧邻分类器 -KNN

遗传算法在ＭＡＴＬＡＢ环境中的实现.rar-genetic algorithm in MATLAB environment is achieved. Rar

the matlab code of ginisvm - an svm implementation good at probability regression.-the matlab code of ginisvm- an svm implementation good at probability regression.