A BI-TODIM Approach Used for Heterogeneous Information Fusion

Shuangming LI; Xin GUAN; Xiao YI; Bin WU

doi:10.11999/JEIT200038

Volume 43 Issue 5

May 2021

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Shuangming LI, Xin GUAN, Xiao YI, Bin WU. A BI-TODIM Approach Used for Heterogeneous Information Fusion[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1282-1288. doi: 10.11999/JEIT200038

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Shuangming LI, Xin GUAN, Xiao YI, Bin WU. A BI-TODIM Approach Used for Heterogeneous Information Fusion[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1282-1288. doi: 10.11999/JEIT200038

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A BI-TODIM Approach Used for Heterogeneous Information Fusion

doi: 10.11999/JEIT200038

Shuangming LI^{1, 2
,
,},
Xin GUAN¹,
Xiao YI¹,
Bin WU¹

1.
Naval Aviation University, Yantai 264001, China
2.
PLA Unit 92941, Huludao 125001, China

Funds: The National Defense Science and Technology Excellence Youth Talent Fund (2017-JCJQ-ZQ-003), The Taishan Scholar Engineering Special Fund (ts 201712072)

Received Date: 2020-01-09
Rev Recd Date: 2020-10-23

Available Online: 2020-12-07

Publish Date: 2021-05-18

Abstract

Abstract

A the Interative Multi-criteria Decision making based on Belief Interval (BI-TODIM) approach is proposed to solve the fusion decision problem of heterogeneous information with mixed type data and expert knowledge. According to the construction theorem of trust interval and grey relation method, the trust interval of mixed type data of unknown target is constructed. The equivalence relationship between trust interval and intuitionistic fuzzy number is clarified. The recognition decision model of mixed type data and expert knowledge is established. The unified expression of feature layer information and decision layer information is realized. The shortcomings of the Technique for Order Preference by Similarity to Ideal Solution based on Belief Function (BF-TOPSIS) method are analyzed such as the inversion phenomenon and the complexity. To solve this problem, the order relation of interval numbers is defined, the BI-TODIM recognition decision method and the method of calculating unknown weight based on intuitionistic fuzzy entropy are proposed. The effectiveness of the proposed method in resolving ranking inversion and heterogeneous information fusion is verified by an example and a target identification case, which underlines low time complexity, good stability and high recognition accuracy.
- Belief interval,
- Interative multi-criteria,
- Heterogeneous information,
- Distance measure,
- Correlation coefficient

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References(16)

References

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