▍1. AnPElectronicPVoltagePTransformer
基于WLAN技术的电压传送技术 主要讲解WLAN的应用(WLAN application mainly on voltage transmission technology based on WLAN technology)
更多选项
▍2. pso-clustering
改进的粒子群分簇路由协议matlab代码，可以在这个基础之上改进(Improved particle swarm clustering routing protocol matlab code can be improved in this basis)
▍3. dynamic-channel-allocation
该程序实现了基于遗传免疫算法的动态信道分配算法(Immune algorithm based on genetic dynamic channel assignment algorithm)
▍4. data-and-case
数据挖掘多个算法及数据，包括关联规则，基本分析、聚类分析、决策树、神经网络、统计方法等(Data mining algorithms and data, including association rules, fundamental analysis, cluster analysis, decision trees, neural networks, statistical methods)
▍5. PSO
mathematica编写的标准粒子群优化（PSO）程序(the mathematica written standard particle swarm optimization (PSO) program)
▍6. Synchronization
混沌同步的经典书籍，上千次被引用。剑桥大学出版社出版。(Chaos synchronization of the classic books, thousands of references. Cambridge University Press.)
▍7. MCMC-Bayesian-(2)
一篇硕士学位论文，对贝叶斯中的mcmc方法论述得比较清楚(A master' s degree thesis, discusses the mcmc the Bayesian method was clearly)
▍8. New-folder-(3)
this ia related forward error correction code and these are used in space communication
▍9. MOPSOwang
关于模糊车辆路径问题的多目标粒子群算法，里面有作者提出的实数编码方式，在经典的MOPSO基础上完成的。模糊包括模糊需求、模糊旅行时间和模糊服务时间多重模糊特性。(Fuzzy vehicle routing problem with multi-objective particle swarm algorithm, which has the real number encoding, proposed by the authors in classic MOPSO based on. Fuzzy fuzzy demand, fuzzy multi-fuzzy features of the travel time and fuzzy service time.)
▍10. Multi-class-SVM-Image-Classification
基于神经网络的遥感图像分类取得了较好的效果,但存在固有的过学习、易陷入局部极小等缺点.支持向量机机器学习方法,根据结构风险最小化(SRM)原理,表现出很多优于其他传统方法的性能,本研究的基于多类支持向量机分类器的遥感图像分类取得了达95.4 的分类精度.但由于遥感图像分类类别多,所需训练样本较大,人工选择效率较低,为此提出以人工选择初始聚类质心、C均值模糊聚类算法自动标注训练样本的基于多类支持向量机的半监督式遥感图像分类方法,期望能在获得适用的分类精度的基础上有效提高分类效率(Neural net based remote sensing image classification has obtained good results. But neural net has inherent flaws such as overfitting and local minimums. Support vector machine (SVM), which is based on Structural Risk Min- imization(SRM), has shown much better performance than most other existing machine learning methods. Using mul- ti-class SVM classifier high class rate of 95.4 is obtained. But for the class number of remote sensing image is much great, manually obtaining of training samples is a much time-consuming work. So a multi-class SVM based semi-super- vised approach is presented. It is choosed that the initial clustering centroids manually first, then label the samples as the training ones automatically with fuzzy clustering algorithm. It is believed that this method will upgrade the classifi- cation efficiency greatly with practicable class rate)
▍11. Model-for-waves-guided
The Semi-Analytical Finite Element SAFE method is becoming established as a convenient method to calculate the properties of waves which may propagate in a waveguide which has arbitrary cross-sectional shape but which is invariant in the propagation direction.(Finite element model for waves )
▍12. hackers-guide
黑客秘籍(chm版）共10本，仍在不断完善中。(Hacker s guide(chm), 10 books)
▍13. Intro_to_Data_Mining
数据挖掘与知识发现介绍 第三版 概念性介绍 英文版(introduction to data mining)
▍14. RPEM_Source_Code
RPEM算法在聚类分析中比ＥＭ算法更好效果。(RPEM algorithm in clustering analysis of better results than EM algorithm.)
▍15. he_book
复杂网络的重要资料,通过它可以了解这个学科，掌握基本的工具(some materials on complex network)
▍16. GA-BP
基于混合神经网络和遗传算法的故障诊断系统，好的文献(Based on hybrid neural networks and genetic algorithms for fault diagnosis system, a good literature )
▍17. N-GEN-(11)
The proposed approach is based on three stages which (1) use neural networks for constructing a response function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating overall performance of a specific factor combination, and (3) use a genetic algorithm to optimize parameter design. Effectiveness of the proposed approach is illustrated with a simulated example. Analysis results reveal that the approach has higher performance than the traditional experimental design.
▍18. NEURO-GENETIC.zip-(4)
The proposed approach is based on three stages which (1) use neural networks for constructing a response function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating overall performance of a specific factor combination, and (3) use a genetic algorithm to optimize parameter design. Effectiveness of the proposed approach is illustrated with a simulated example. Analysis results reveal that the approach has higher performance than the traditional experimental design.
▍20. Internet-Protocols
this book is called as internet protocol that will tell us about the internet protocol
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