Abstract
The aim of this paper is to introduce an alternative Pattern Recognizing technique using similarity measure in the spherical fuzzy set environment. In many applications of pattern recognition, the structural data is intrinsically ambiguous. It is essential to boost the descriptive power of pattern recognition in such applications, and the fuzzy technique is often used. So, a fuzzy logic (FL)-based similarity measure (SM) called Exponential similarity measure for Spherical fuzzy sets (SFSs) is applied in the field of Pattern Recognizing. In this paper similarity measures known as Exponential Similarity Measure (ESM), Weighted Exponential Similarity Measure (W-ESM), Weighted Average Exponential Similarity Measure (WA-ESM), Weighted Generalized Average Exponential Similarity Measure (WGA-ESM) are developed. Spherical fuzzy set is extended from fuzzy sets to cope with uncertain situations more accurately. Further, a problem on Intrusion Detection and Risk evaluation is chosen as an application of pattern recognition and is solved using similarity measures proposed in this paper.
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Ajay, D., Pon Hidaya David, P. (2022). Exponential Similarity Measure for Spherical Fuzzy Sets and Its Application in Pattern Recognition. In: Bhateja, V., Tang, J., Satapathy, S.C., Peer, P., Das, R. (eds) Evolution in Computational Intelligence. Smart Innovation, Systems and Technologies, vol 267. Springer, Singapore. https://doi.org/10.1007/978-981-16-6616-2_41
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DOI: https://doi.org/10.1007/978-981-16-6616-2_41
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