Abstract
As a hybrid fuzzy extension of the complex non-linear Diophantine fuzzy set, the complex non-linear Diophantine fuzzy hypersoft set was developed by fusing it with the hypersoft set. To address multi-sub-attributed real-world similarity problems within complex non-linear Diophantine fuzzy ambiance, this study proposes distance measures and five innovative similarity measures such as Jaccard similarity measure, exponential similarity measure, cosine similarity measure, similarity measure based on cos function, and similarity measure based on cot function for complex non-linear Diophantine fuzzy hypersoft set. Furthermore, based on proposed similarity measures, a highly effective algorithm is provided for handling decision-making issues exquisitely in the pattern recognition field, along with an illustrative example of mineral identification. Then, to demonstrate the validity, reliability, robustness, and superiority of the proposed notion and algorithm, a detailed comparative study with proper discussion has been presented in the study.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
