A branch

混合生源 加工-Mixed biogenic processing

人工智能的一种典型的启发式搜索算法，是一种最好优先的算法，但要加上一些约束条件。-A typical artificial intelligence heuristic search algorithm, is a priority of the best algorithm, but to add some more restrictive conditions.

人工智能学习的重要内容，对加强和巩固所学内容将起到非常重要的作用。-AI an important part of learning, to strengthen and consolidate the contents will play a very important role.

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,

计算机网络经典算法：生产者与消费者问题的源代码-classic algorithm of computer network:producer and consumer

蚂蚁算法，c语言版，其中，‘F’点表示食物，‘H’表示窝，白色块表示障碍物，‘+’就是蚂蚁了。-Ant algorithm, c language version, of which,

〈智能优化算法与应用〉介绍各种优化算法：模拟褪火法、遗传算法、禁忌搜索法、神经网络法、混合优化策略等内容。-"intelligent optimization algorithms and application" on the various optimization algorithms : simulated fire faded, genetic algorithm, Tabu search method, neural networks, hybrid optimization strategy content.

根据教材整理的神经网络程序！很多种神经网络程序-Finishing materials in accordance with the neural network program! A variety of neural network procedures

用Java编的人工智能的归结反演算法-Java series attributed to the anti-artificial intelligence algorithms

tsp问题，是一个很典型的NP完全问题，该程序用了遗传―退火结合算法，能优化计算-tsp problem is a typical NP-complete problem, the program is to use genetic- combined annealing algorithms that optimize computing