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Open Access

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

Jun Xia, Yuqiang Feng( ), Luning Liu( ), Dongjun Liu
School of Management, Harbin Institute of Technology, Harbin 150001, China.
Shenzhen Institute of Electronics, Shenzhen 518055, China.
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Abstract

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.

Keywords

big datadecision makinginformation fusioninnovation allianceBayesian networksforecasting model

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Tsinghua Science and Technology
Volume 23 Issue 3,
June 2018
Pages 347-356
DOI: 10.26599/TST.2018.9010079
Cite this article:
Xia J, Feng Y, Liu L, et al. An Information Fusion Model of Innovation Alliances Based on the Bayesian Network. Tsinghua Science and Technology, 2018, 23(3): 347-356. https://doi.org/10.26599/TST.2018.9010079

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Received: 21 December 2017
Accepted: 22 January 2018
Published: 02 July 2018
© The author(s) 2018
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