Peers Attribute Data Prediction in a P2P Network Based on the Grey Prediction Model and Its Improvements

摘要：

A Prediction Model and two improved models are proposed and analyzed in this paper, aiming to solving the task of peers attribute data prediction in a p2p network. The simulation results demonstrate that the Basic Grey Prediction Model performs well under the condition that the accumulation of Raw Data Series complies with the positive or negative growth of an exponential function. When this condition cannot be satisfied, the Residual Error Improvement Model can significantly increase the accuracy of the prediction. Additionally, the Grey Prediction Model with New Dynamic Information of Equal Dimension is suitable when the long term prediction is concerned.

关键词： p2p peer attribute grey prediction models

作者: Wang Jiechao Zhang Yidan

作者单位: International School Beijing University of Posts and Telecommunications Beijing, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information,Networking and Automation(2010 IEEE信息网络与自动化国际会议 ICINA 2010)

会议地点: 昆明

会议语种:英文

页码: 15-19

在线出版日期: 2010-10-17（万方平台首次上网日期，不代表论文的发表时间）