人事管理系统（java数据库课程设计）+SQL数据库

基于RLS和LMS的自适应滤波器的MATLAB代码，带有中文注释

可以让你把别人网站的代码全部给复制下来，包括css，php等文件

易语言热血江湖登录器模块

使用matlab 进行图像质心计算，用于计算质心。

实现指纹识别中的指纹图像预处理中的方向场，细化等，含有一个GUI界面.

pdf文档，中文来源：华北电力大学学报242007[11997199811.2199910.88408200.68000.47800.2掩76072007000100120时间/天68040100120图3训练过程中的误差变化时间/天Fig.3 Errors during training图1日负荷预测时洲练数据4Fig. 1 Training data for day load for ecas ting35←只51.5050-10203040如0的070809010101200.8时间压图4训练过程中神经元个数变化Fig 4 Grow th of neurons during train ing0.200.95系0.940.8505101520253035滞后时间/天如0.80.75图2训练数据的自相关系数Fig. 2 Autocorrelation coefficients of training dat a(a拟合曲线0.〔(3)10.040.0系70/14060[1000000]时间/天(b拟合误差「O1000001图5训练结果及误差Fig. 5 Result and error of train in3- EBF6,C1994-2012cHinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net4EUNITE2582080078076074072026.26700(3)66005101520253035时间/天50/1[00001图6日最大负荷预测结果[01010]26ig. 6 Result of forFrecasting g1 SOFNN[716.2,739.7,757.7,781.3],7Tab 1 Accuracy of training and forecast ing[720.1,738.2,763.7,MethodMAPE/ (%O) ME767.7],7SOFNN1.3344.137901.7850.04780EUNITE1.95E770760winner750报告中ME值没有准确堤供,但可以从报告中估轵740计得出约50~60完整的 EUNITE网络竟赛原始数据可730从EUNITE网站获得(http://neuron.tuke.sk/compe-720tit ion/ index. php)7103354EUNITEMAPE时间1.95[2]图7周平均最大负荷预测结果3.2Fig. 7 Forecasting result of week average max loadSOFNNSOFNNWSj72SOF NNWLWLideltaWli, delta WLi=WLj-Wli(3h:× delt al+k× deltal wj,Yh=0.58o1994-2012ChinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp:/www.cnki.net262007820[1] Chen B J, Chang M W, Lin C J. Load forecasting using800support vector machines: a study on eunitE com-780tion 2001[J]. IEEE transactions on power systems7602004.19(4):1821-1830[2] Company behind East- Slov akia Power Distrib ution740Com panWorle w ide com petition w ithin the EU720NITE network, EUNITE competiton report [RI700[3]6802004.28(17):1-1105101520253035[4 Leng g, Prasad g, McGinnity T M. An on line algor-时间/天rithm for creating self organ izing fuzzy neural networ ks图8修正后的日最大负荷预测结果Neural Netw orks, 2004,(17): 1477-1493[5 Ort iz: Arroyo D, Skov M K, Huynh Q. Accurate Elee-F ig.8 Forecasting results after rev sedtricity Load Forecasting with Artificial Neur al NetworksIC. Proceedings of the 2005 International Conference2SOFNNon Compu tat io nal Intel ligence for M odel ling, Control andTah 2 Accuracy of forecast ingAuto mation. and International Conference on I ntelligentMethodMAPE/(%)MEAgents, Web Technolo gies and Internet CommerceSOFNN1.7850.04(CIMCAIA WTIC 05). 20051.5941.95[ 6] Tao X. Input dimens ion reduction for load forecastingEUNITE1.9550-60based on support vector machines [C]. Hong Kong82004 IEEE International Conference of Electric U til yderegulation, res tructur ing and pow er technolog iesMAPE ME20[7 Hsu CC. Dynam icall y Optim izing Parameters in SupportVector Regression An A pp licat io n of Electricity Load4结论Forecasting [C]. Haw aii: Proceedings of the 3 9thIlaw aii International Conference on System Sciences199918 Pan kratz A. Forecasting w ith Univariate Box-JenkinsModels [m. John Wiley sons, 1983SOFNN(1972-),,C1994-2012cHinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net

基于JPBC的SM9算法的java实现，实现SM9算法的所有部分。包括主密钥对的生成，用户私钥生成；签名验签算法，密钥封装解封算法，数据加密解密算法，密钥交换算法；以及对《GMT 0044-2016 SM9标识密码算法：第5部分》测试的验证。

从visio简介，常用操作规范，流程实例介绍，组织结构图简介以及常见图表举例等几个角度全面的对VISIO进行说明。

利用多维高斯混合模型，建立背景，然后通过减背景获得前景区域，多维高斯混合模型具有较强的抗噪声，较好适应光线变化

【实例简介】有一个承重为W的背包和n个物品，它们各自的重量和价值分别是wi和vi（1