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Fuzzy Clustering for Classification of Metamaterial Properties
Abstract
Metamaterials are a class of artificially engineered materials that exhibit unique physical and electromagnetic properties not found in natural materials. Fuzzy clustering is a machine learning technique that can be used to classify metamaterials based on their physical and electromagnetic characteristics. In this chapter, the authors provide an overview of metamaterial properties and classification challenges and introduce the basics of fuzzy clustering and its application in material classification. They then present a proposed approach for metamaterial classification using fuzzy clustering, along with case studies demonstrating the effectiveness of this approach. They discuss the potential applications of metamaterial classification and how it can support the development of new metamaterial applications. This chapter provides a valuable resource for researchers and students interested in using fuzzy clustering to classify metamaterials based on their physical and electromagnetic properties.
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