▍1. A-Fast--Method-Based-on--DFT-
电力系统谐波检测，包括傅里叶级数，小波变换，神经网络(A Fast Harmonic Detection Method Based on Recursive DFT )
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▍2. buchblock
一本关于广义度量化空间、神经网络以及微分方程的研究书(In mathematics, general topology or point-set topology is the branch of topology which studies properties of topological spaces and structures defined on them.An important consideration in non-linear analysis is the question of uniqueness. For a network composed of linear components there will always be one, and only one, unique solution for a given set of boundary conditions。Another important consideration is the question of stability.)
▍3. 22
说明： 通过这种方法能够进行故障的寻找和定位,实例分析的结果说明了利用粗糙集进行知识发现及建立智能故障诊断系统的可行性和有效性.(Some work has been done for dealing with Fault Detection and Diagnosis (FDD) based on Rough Set, but in those cases Rough Set was just regarded as a tool for data cleaning or for assisting of)
▍4. 16
说明： 利用粗糙集理论对决策表进行约简以自动获取过程工业生产系统中的故障知识,从信息熵的角度分析系统知识不确定性的变化,提出了一种基于粗糙集理论的故障诊断新方法,研究了粗糙集理论在故障诊断中的适用性,在前向推理和反向推理的基础上(Some work has been done for dealing with Fault Detection and Diagnosis (FDD) based on Rough Set, but in those cases Rough Set was just regarded as a tool for data cleaning or for assisting of other methods, or for detecting whether a system has fault)
▍5. 15
说明： 利用粗糙集理论对决策表进行约简以自动获取过程工业生产系统中的故障知识,从信息熵的角度分析系统知识不确定性的变化,提出了一种基于粗糙集理论的故障诊断新方法,研究了粗糙集理论在故障诊断中的适用性,在前向推理和反向推理的基础上(Some work has been done for dealing with Fault Detection and Diagnosis (FDD) based on Rough Set, but in those cases Rough Set was just regarded as a tool for data cleaning or for assisting of other methods, or for detecting whether a system has fault but usually cannot tell where it happened.To solve this problem, a n)
▍7. pso-paper
基于粒子群算法的电力系统经济负荷分配研究(Based on particle swarm optimization of power system economic load allocation study)
▍8. 1.chaos_paper1
1.Experimental realization of a highly secure chaos communication under strong channel noise
▍9. SVM-Multiregression
SVM Multiregression for Non Linear Channel Estimation in Multiple-Input Multiple-Output Systems 在多输入多输出系统中的SVM多元回归非线性逼近(This paper addresses the problem of Multiple-Input Multiple-Output (MIMO) frequency non-selective channel estimation. We develop a new method for multiple variable regression estimation based on Sup- port Vector Machines, a state-of-the-art technique within the machine learning community for regression estimation. We show how this new method, that we call M-SVR, can be effi ciently solved. The pro- posed regression method is evaluated in a MIMO system under a channel estimation scenario, showing its benefi ts in comparison to previous proposals when non linearities are present in either the transmitter or the receiver sides of the MIMO system.)
▍10. adaptive-genetic-algorithm
自适应GA SVM 参数选择算法研究Param eter selection algorithm for support vector machines based on adaptive genetic algorithm 支持向量机是一种非常有前景的学习机器, 它的回归算法已经成功地用于解决非线性函数的逼近问题. 但 是, SVM 参数的选择大多数是凭经验选取, 这种方法依赖于使用者的水平, 这样不仅不能获得最佳的函数逼近效果, 而且采用人工的方法选择 SVM 参数比较浪费时间, 这在很大程度上限制了它的应用. 为了能够自动地获得最佳的 SVM 参数, 提出了基于自适应遗传算法的 SVM 参数选取方法. 该方法根据适应度值自动调整交叉概率和变异概率, 减少了遗传算法的收敛时间并且提高了遗传算法的精度, 从而确保了 SVM 参数选择的准确性. 将该方法应用于船用 锅炉汽包水位系统建模, 仿真结果表明由该方法所得的 SVM 具有较简单的结构和较好的泛化能力, 仿真精度高, 具 有一定的理论推广意义.( The support vector m achine ( SVM ) is a prom ising artificia l inte lligence technique, in w hich the regres sion a lgorithm has a lready been used to so lve the nonlinear function approach successfully. Un fortunate ly, m ost us ers se lect param eters for an SVM by ru le o f thumb, so they frequently fail to generate the optim al approach ing e ffect for the function. Th is has restricted effective use o f SVM to a great degree. In order to get optim a l param eters auto m atically, a new approach based on an adaptive genetic a lgorithm ( AGA ) is presented, w hich autom atica lly ad justs the param eters for SVM. This m ethod se lects crossover probability and mutation probab ility accord ing to the fitness va lues of the object function, therefo re reduces the convergence tim e and im proves the prec ision o fGA, in suring the accuracy of param eter se lection. Th is m ethod w as applied to m odeling of w ater level system o f a sh ip b)
▍11. Machines-Based-on-DFS
深度优先搜索的支持向量机参数优化算法 Study on Parameters Optimization of Support Vector Machines Based on DFS :研究支持向量机参数优化问题，由于算法要求准确选择 SVM 参数，支持向量机在处理大样本数据集时和最优模型参 数确定时，消耗的时间长、占有内存大，易获得局部最优解的难题。为了解决支持向量机存在的不足，采用深度优先搜索算 法对其参数优化机机制进行改进。将向量机参数优化视成一个组合优化问题，将支持向量机模型的分类误差作为优化目标 函数，采用深度优先算法对其进行求解，最后将模型应用于 3 个标准分类数据集。仿真结果表明，优化参数后的支持向量机 加快模型的训练速度度，提高了分类的准确率，很好的解决( Study on the problems of support vector machines parameters optimization． The prediction precision of Support vector machines model and generalization ability depend on its parameters reasonable choice． The problems of time － consuming and easy falling into the local optimal value exist in traditional support vector machine parameters optimization algorithm，and support vector machine prediction precision is low． In order to solve the problems，the paper puts forward a method based on depth first search of SVM parameters optimization method ( DFS － SVM) ． DFS － SVM takes SVM parameters optimization as a combinatorial optimization problem and the RMSE as optimization goal，uses depth first search to select SVM parameters，and tests DFS － SVM performaces through three standard data set． Simulation experiment results show that the DFS － SVM prediction accuracy is improved and the training time is shorten greatly． It provides a new effective solution for SVM parameters optimizat)
▍12. bp
说明： 一种采用增加动量项的改进BP算法，是对BP算法的一种改进算法(One kind of items used to increase the momentum of improved BP algorithm is an improved algorithm of BP algorithm)
▍13. matlab-book
本书系统介绍MATLAB遗传算法和直接搜索工具箱的功能特点、编程原理及使用方法。全书共分为9章。第一章至第四章介绍遗传算法的基础知识，包括遗传算法的基本原理，编码、选择、交叉、变异，适应度函数，控制参数选择，约束条件处理，模式定理，改进的遗传算法，早熟收敛问题及其防止等。第五章至第七章介绍英国设菲尔德（Sheffield）大学的MATLAB遗传算法工具箱及其使用方法，举例说明如何利用遗传算法工具箱函数编写求解实际优化问题的MATLAB程序。第八章和第九章介绍MathWorks公司最新发布的MATLAB遗传算法与直接搜索工具箱及其使用方法。(This file describes changes to the Solr Cell (contrib/extraction) module. See SOLR-284 for details.)
▍14. Fuzzy-Decision-Tree-Algorithms
Fuzzy Decision Tree Algorithms
▍15. Fuzzy-Mathematics-and-Applications
第一章介绍模糊集合的基本概念、建立模糊集合隶属度函数的基本方法以及Matlab模糊工具箱中的函数的应用。第二章判别分析方法包括距离判别、模糊集合的贴近度判别以及最大隶属原则。第三章在模糊矩阵概念的基础上，给出了模糊聚类的基本方法以及模糊C均值聚类的Matlab实现。第四章模糊综合评价，建立了客观性权向量、模糊矩阵的综合评价方法。第五章层次分析法介绍了模糊层次分析的建模方法与应用。第六章在普通线性规划的基础上，引入模糊线性规划、多目标规划的模糊最优解以及模糊线性规划在经济中的应用实例。 本书主要对象是财经类院校本科生，可以作为数学建模第二课堂的辅导教材，也可供硕士研究生以及科技工作者参考。(The first chapter introduces the basic concepts of fuzzy sets, fuzzy set membership function to establish the basic methods and functions in the Matlab fuzzy toolbox application. Chapter sub-discriminant analysis, including distance Do not, determine closeness of fuzzy sets and the maximum membership principle. The third chapter in the fuzzy matrix based on the concept, given the basic methods of fuzzy clustering and fuzzy C means clustering of the Matlab implementation. S Fuzzy comprehensive evaluation of four chapters, the establishment of the objectivity of the weight vector, fuzzy comprehensive evaluation matrix. Chapter V describes the fuzzy AHP AHP modeling methods and applications. Chapter VI in the general linear Planning based on fuzzy linear programming, multiobjective programming and fuzzy optimal solution of fuzzy linear programming application example in the economy. This book is the main target of Financial College undergraduates, mathematical modeling can be used)
▍16. Immune-genetic-algorithm
基于改进免疫遗传算法的配电网重构，该文章系统的讲解了运用改进免疫遗传算法对配电网重构，并有详细的程序设计步骤，对相关领域的研究者有一定的参考价值(Immune genetic algorithm based on improved distribution network reconfiguration, the article explains the use of the system to improve the immune genetic algorithm for distribution network reconfiguration, and detailed design steps of the procedure, researchers in related fields with some reference value )
▍17. dhjdifjj
UKF算法及其在纯方位目标跟踪中的应用，改进 无迹卡尔曼滤波(UKF algorithm and its only target tracking application, unscented Kalman filter to improve)
▍18. Adhoc
针对家庭网络组网的业务和服务特点，根据OSI模型，在深入研究数据链路层信道共享技术中MAC层CSDN/CA协议及其DCF机制和MAC层协议的信道利用率的基础上，提出了一种基于Adboc模式的无线家庭网络分层模型，设计出一个用于家庭网络节点间通信的通信子网，包括物理层，数据链路层和网络层，并对物理层传输技术，链路层信道共享技术以及网络层路由技术进行了分系和设计。(For a home network characteristics of network operations and services, according to OSI model, in-depth study of channel sharing the data link layer MAC layer technology CSDN/CA protocol and DCF MAC layer protocol mechanism and the channel utilization, based on the proposed Adboc model based hierarchical model of a wireless home network, to design a home network node communication for the communication subnet, including the physical layer, data link layer and network layer and physical layer transmission technology, link layer channel sharing technology and network layer routing technology and design of sub systems.)
▍19. zuidasiranbisuanfa
说明： 针对MPSK信号的调制识别问题，本文提出了一种新的最大似然比调制分类算法，采用平均释然比检测方法，通过对接收信号的的离散化和对主要参数的简要近似，得到了离散情况下的近似分类统计量！(MPSK signals for modulation recognition problem, we propose a new maximum likelihood modulation classification algorithm, using an average of more than relieved detection method, the received signal by the discrete and approximate summary of the main parameters obtained discrete case statistics under the approximate classification!)
▍20. jianfeiderengongshenjingwangmoxing
说明： 本文通过分析影响减肥的因素，建立减肥演算的BP神经网络模型，运用动量阶梯下降算法，L-M优化算法和贝叶斯正规算法对减肥过程进行模拟和预测。(mathematical model about lose weight )
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