Abstract
With the development of digital TV, especially 3D technologies, some applications in the digital home industry have been reported to meet and even exceed customer expectation in the market place for enterprise. In order to evaluate the clothing comfort performance in the digital e-commerce service, the clothing comfort model is very important. Considered the physical, physiological and psychological factors, a theoretical clothing comfort evaluation model is presented based on the adaptive fuzzy neural network in this paper. According to the characters of clothing comfort, Fuzzy Neural Networks (FNN) can provide a very human machine knowledge representation scheme friendly for acquiring, representing and using the knowledge of the domain expert. This is a significant advantage for clothing comfort evaluation where the exact system transfer functions cannot be well modeled and adequate training data sets are not available. The experiment results shown that there has the same prediction trend about the experiment result and simulation result. This clothing comfort evaluation model is used as a component in the smart clothing function user experience system.
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Acknowledgements
This research is supported by the National Natural Science Foundation of China(61073131), NSFC-Guangdong Joint Fund (No. U1135003, U0935004), the National Key Technology R&D Program (No. 2011BAH27B01, 2011BHA16B08), the Industry-academy-research Project of Guangdong (No. 2011A091000032).
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Wang, R., Du, H., Zhou, F. et al. An adaptive neural fuzzy network clothing comfort evaluation model and application in digital home. Multimed Tools Appl 71, 395–410 (2014). https://doi.org/10.1007/s11042-013-1519-4
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DOI: https://doi.org/10.1007/s11042-013-1519-4