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A Survey of Homogeneous and Heterogeneous Multi-source Information Fusion Based on Rough Set Theory

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Artificial Intelligence and Machine Learning (IAIC 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2058))

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Abstract

Multi-source information fusion (MSIF) can be defined as the process of automatically analyzing and synthesizing information and data from multiple sensors or sources based on certain standards so as to achieve the required decisions and estimates, and it includes two types of information, homogeneous information and heterogeneous information. MSIF is also referred as multi-sensor information fusion. Rough set theory (RST) provides an effective method to process uncertain, inaccurate, or incomplete data. Therefore, many homogeneous and heterogeneous MSIF approaches based on RST have been put forward. In this paper, we summarize the homogeneous and heterogeneous MSIF based RST. Firstly, we introduce the background knowledge of rough set theory and multi-source information fusion. Secondly, we classify the existing homogeneous and heterogeneous MSIF models based on RST. Then, we discuss these MSIF models and summarize their application scenarios. At the end of this paper, we propose the challenges and future trends of homogeneous and heterogeneous MSIF based on RST from the perspectives of data processing and privacy security.

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Acknowledgements

This work was supported by Hainan Provincial Natural Science Foundation of China (Grant No. 620MS021), National Natural Science Foundation of China (NSFC) (Grant No. 62162022,62162024), the Major science and technology project of Hainan Province (Grant No. ZDKJ2020012), Youth Foundation Project of Hainan Natural Science Foundation(621QN211).

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Authors and Affiliations

  1. School of Computer Science and Technology, Hainan University, Haikou, 570228, China

    Haojun Liu, Xiangyan Tang & Taixing Xu

  2. School of Engineering and Information Science, University of Wollongong, Wollongong, 2500, Australia

    Ji He

  3. Hainan Blockchain Technology Engineering Research Center, Haikou, 570228, China

    Haojun Liu & Xiangyan Tang

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  1. Haojun Liu
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  2. Xiangyan Tang
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  4. Ji He
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Correspondence to Xiangyan Tang .

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Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, Hubei, China

    Hai Jin

  2. Chinese Academy of Science, Shenzhen, China

    Yi Pan

  3. Nanjing University of Science and Technology, Nanjing, China

    Jianfeng Lu

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Liu, H., Tang, X., Xu, T., He, J. (2024). A Survey of Homogeneous and Heterogeneous Multi-source Information Fusion Based on Rough Set Theory. In: Jin, H., Pan, Y., Lu, J. (eds) Artificial Intelligence and Machine Learning. IAIC 2023. Communications in Computer and Information Science, vol 2058. Springer, Singapore. https://doi.org/10.1007/978-981-97-1277-9_18

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  • DOI: https://doi.org/10.1007/978-981-97-1277-9_18

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