Ant Algorithm js realize some time ago in the online collection

机器人编程方法，主要是讲c的， 期刊论文-Robot programming method, mainly stresses c and Journal Papers

昨天刚刚看到的A star算法类的实现，不知道对大家有没有用，参考一下吧-Yesterday, I saw a star of the algorithm to achieve category, we do not know of any use it for reference

PID仿真参考书,关于神经网络等方面的书，应用广泛。希望大家积极下载。-PID simulation of reference books, such as neural networks on the books, a wide range of applications. Hope that we actively download.

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

tsp问题用神经网络方法解决-tsp uses neural network solution

gasample遗传算法代码-gasample genetic algorithm code

遗传编程是一门新兴的进化计算技术且引起了学术界的非常高的重视。虽然本程序是本人编写，略显粗糙，但需要的人还是可以借鉴一下！-Genetic programming is an emerging technology of evolutionary computation and has aroused increasing attention, although this code is done by myself, it can serve as a reference for anyone needs it!

用人工智能实现的足球机器人人仿真比赛的程序-using artificial intelligence robot soccer simulation games who procedures

用C++实现遗传算法求解TSP问题.txt-C++ for TSP

目标函数是De Jong函数，是一个连续、凸起的单峰函数-Objective function is De Jong function, is a continuous, convex function of the single-peak