Yu Y.Hui C.-L.TSAN MING CHOIAu R.2022-05-302022-05-302010https://www.scopus.com/inward/record.uri?eid=2-s2.0-77958152376&doi=10.1109%2fTSMCC.2010.2045121&partnerID=40&md5=53af309d277ac5f87e328b8f2972973bhttps://scholars.lib.ntu.edu.tw/handle/123456789/612392Fabric 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. ? 2006 IEEE.Artificial neural network (ANN); fabric hand prediction; fuzzy logic; fuzzy neural network (FNN)Artificial intelligence methods; Artificial Neural Network; Fabric hand descriptors; fabric hand prediction; Feature selection; FNN models; Future research directions; fuzzy neural network (FNN); Intelligent fabrics; Interpretability; Network structures; Prediction accuracy; Prediction systems; Real data sets; Artificial intelligence; Feature extraction; Forecasting; Fuzzy neural networks; Fuzzy systems; Product development; Fuzzy logicjournal article10.1109/TSMCC.2010.20451212-s2.0-77958152376