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Design of fuzzy set-based deep fusion algorithm for multi-sensor data

 oraz   
21 mar 2025

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Figure 1.

The Process Chart of Data Fusion
The Process Chart of Data Fusion

Figure 2.

Filtering effect
Filtering effect

Figure 3.

The fusion result is compared to the original data
The fusion result is compared to the original data

Figure 4.

The target recognition success rate of four evidence was compared
The target recognition success rate of four evidence was compared

Dynamic bending distance calculation and weighted value

Dynamic bending distance Node 1 Node 2 Node 3 Support value The value of its own reliability Final fusion weighted value
Node 1 0 11.23 5.70 0.220 0.322 0.213
Node 2 11.23 0 6.40 0.299 0.333 0.291
Node 2 5.70 6.40 0 0.481 0.345 0.496

Comparison of the four evidence of the fusion

Method m(A) m(B) m(C) m(Φ)
Yager 0.3880 0 0.000034 0.6120
Dempster 0.9991 0 0.000086 0
Murphy 0.9994 0.000022 0.000648 0
Zhang 0.9994 0.000022 0.000322 0
Ghiasi 0.5146 0 0.000495 0
Ours 0.9996 0.00000009 0.000006 0
Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne