An Information Fusion Model of Innovation Alliances Based on the Bayesian Network

作     者：Jun Xia Yuqiang Feng Luning Liu Dongjun Liu 

作者机构：School of Management Harbin Institute of TechnologyHarbin 150001 China. Shenzhen Institute ofElectronics Shenzhen 518055 China 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2018年第23卷第3期

页      面：347-356页

核心收录：

学科分类：08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 

基　　金：supported by the National Natural Science Foundation of China(Nos.71472053 71429001 and91646105) 

主　　题：information fusion innovation alliance Bayesian networks forecasting model decision making big data 

摘      要：To solve the problem of information fusion from multiple sources in innovation alliances, an information fusion model based on the Bayesian network is presented. The multi-source information fusion process of innovation alliances was classified into three layers, namely, the information perception layer, the feature clustering layer,and the decision fusion layer. The agencies in the alliance were defined as sensors through which information is perceived and obtained, and the features were clustered. Finally, various types of information were fused by the innovation alliance based on the fusion algorithm to achieve complete and comprehensive information. The model was applied to a study on economic information prediction, where the accuracy of the fusion results was higher than that from a single source and the errors obtained were also smaller with the MPE less than 3%, which demonstrates the proposed fusion method is more effective and reasonable. This study provides a reasonable basis for decision-making of innovation alliances.