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MVC设计模式在ASP角色身份验证中应用与实现
引用本文:刘洋.MVC设计模式在ASP角色身份验证中应用与实现[J].教育技术导刊,2009,19(8):35-37.
作者姓名:刘洋
作者单位:湖北大学数学与计算机科学学院;
基金项目:基金项目:2007年度甘肃省教育信息化发展战略项目(甘教信办[2007]1号);国家社会科学“十一五”规划(教育学科)2007年国家一般课题(BCA060016)子课题
摘    要:介绍了MVC设计模式的思想,以ASP角色身份验证为具体实例,研究了MVC设计模式在角色身份验证的设计与运用,并在此基础上构建了一个基于B/S三层架构的角色身份验证系统。项目实际应用证明采用MVC设计模式能加快系统的开发效率,系统具有较好的扩展性和可维护性,分层架构清晰,耦合度低。

关 键 词:MVC  设计模式  身份验证  耦合度  
收稿时间:2019-11-08

Wireless Propagation Prediction Model Based on XGBoost
ZHU Jia-peng,DUAN Yu-shuai.Wireless Propagation Prediction Model Based on XGBoost[J].Introduction of Educational Technology,2009,19(8):35-37.
Authors:ZHU Jia-peng  DUAN Yu-shuai
Institution:School of Information Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China
Abstract:Traditional wireless propagation models usually need to divide propagation scenarios based on empirical models. In order to solve the problem that it is not accurate enough in practical application,this paper designs and selects the appropriate feature parameters as input to the model through a large number of engineering parameters. The wireless propagation model based on machine learning XGBoost can accurately predict the wireless signal coverage in the new environment. The experimental results show that compared with the long-short memory network(LSTM)and linear regression method,the predicted root mean square error is 9.101,and the error is the smallest. The method of this paper is good in the accuracy of prediction and the robustness of the model. It is of great significance to accurately predict the channel propagation path loss in different scenarios.
Keywords:integrated learning  wireless propagation model  data analysis  feature engineering  
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