Neutrosophic Sets and Systems
Abstract
Smart clothing design turned out to be a set of complex decision-making processes requiring complementary aesthetics, functionality, as well as customer preferences. This, in turn, makes the traditional evaluation methods struggle to deal with uncertainty and subjectivity in customer feedback about smart clothing design. In an attempt to address this challenge, this research article proposes a novel Neutrosophic approach that integrates Interval-Valued Neutrosophic (IVN) with Convolutional Network to build an intelligent tool for the evaluation of smart clothing design choices. The Neutrosophic representation enables modeling uncertainty, inconsistency, and hesitancy in decision-making by assigning interval-ed membership degrees for different views of smart clothes design. Using the interval-valued representations, we enable robust learning and interpretation of user partialities while handling vague feedback. Proof of concept experiments are conducted on a case study for a smart fashion dataset, and the quantitative results and analysis demonstrate that the proposed approach outperforms the standard techniques for smart clothes classification and ranking design choices. The findings from this analysis prove the ability of our approach to facilitate intelligent decision support in the fashion industry.
Recommended Citation
Wu, Fengfang. "Convolutional Interval-Valued Neutrosophic Network for Intelligent Evaluation of Smart Clothing Design Choices." Neutrosophic Sets and Systems 81, 1 (2025). https://digitalrepository.unm.edu/nss_journal/vol81/iss1/28
