smac

这是用Labwindow/cvi编写的基于datasocket技术的网络通信技术，值得一看，对初学者很有帮助(This is prepared by using Labwindow/cvi DataSocket technology based on network communication technology, worth a look, very helpful for beginners)

Gentleboost，这是一种基于信息融合的机器学习源代码，成功应用于多个工程信息领域。(Gentleboost, which is a fusion-based machine learning source code, successfully applied in various projects in the field of information.)

各种粒子群算法代码，有标准粒子群的，混合粒子群的，还有改进粒子群的。修改参数就可用。(A variety of particle swarm algorithm code, standard particle swarm hybrid particle swarm, as well as improved particle swarm. Modify the parameters can be used.)

这是主要完成文件上传功能,对要写ftp程序者是一个好的参考源码-This is the major file upload function, the right to write ftp procedures is a good reference source

采用改进遗传算法优化模糊控制隶属函数，实现隶属度自动寻优(Using improved genetic algorithm to optimize the fuzzy membership function, the membership degree of automatic optimization)

 

说明：  序优化是解决基于仿真优化的重要工具，由著名学者YuChi Ho提出(Ordinal optimization is to solve an important tool for simulation-based optimization, presented by the famous scholar YuChi Ho)

实现了开放环境下的信任管理功能，并能够分析和计算不同实体之间的直接和间接信任值(The realization of an open environment of trust management functions, and be able to analyze and between the different entities of direct and indirect trust value)

说明：  本文是2016 台湾资料科学年会前导课程“一天搞懂深度学习”的全部讲义PPT（共268页），由台湾大学电机工程学助理教授李宏毅主讲。作者在文中分四个部分对神经网络的原理、目前存在形态以及未来的发展进行了介绍。深度学习的每一个核心概念在文中都有相关案例进行呈现，通俗易懂。一天的时间搞懂深度学习？其实并不是没有可能。(This is the entire handout PPT (268 pages in total) of "a day to understand deep learning", the leading course of the 2016 Taiwan annual conference of data science. It was given by li hongyi, assistant professor of electrical engineering at Taiwan university.In this paper, the author introduces the principle, existing form and future development of neural network in four parts.Each core concept of deep learning is presented in relevant cases, which are easy to understand.)

利用T-S模糊神经网络对非线性函数进行逼近，已成功运行，有注释，对学习模糊神经网络帮助很大(Using TS fuzzy neural network for nonlinear function approximation, has been run successfully, Notes, a great help learning fuzzy neural network)