Intelligent fabric hand prediction system with fuzzy neural network

Yong Yu, Chi Leung Hui, Tsan Ming Choi, Raymond Au

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)


Fabric selection is a crucial step in fashion product development. Prior research works have studied the prediction of fabric specimens based on the fabric hand descriptors via either traditional statistical methods or artificial intelligence methods. Despite showing good prediction accuracy, these methods usually lack an understandable ruleset, which means their interpretability is low. In this paper, a fuzzy neural network (FNN) based intelligent fabric hand prediction system is explored. Unlike some traditional FNN models in which a full ruleset of the artificial neural network (ANN) is presumed, the proposed FNN system includes a simplification of the network structure and feature selection, so that the number of rules is significantly reduced without big sacrifice on prediction accuracy. Real datasets collected from 30 participants evaluation on a set of ten fabric specimens are used to train and test the performance of the proposed system. The systems prediction accuracy is found to be over 80. Applications of the proposed system are discussed and future research directions are outlined.
Original languageEnglish
Article number5451119
Pages (from-to)619-629
Number of pages11
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Issue number6
Publication statusPublished - 1 Nov 2010


  • Artificial neural network (ANN)
  • fabric hand prediction
  • fuzzy logic
  • fuzzy neural network (FNN)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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