On-Line Modeling Via Fuzzy Support Vector Machines
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Load forecasting model based on amendment of mamdani fuzzy system
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Fuzzy classifier based on fuzzy support vector machine
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper presents a new version of fuzzy support vector machine (FSVM) developed for product design time estimation. As there exist problems of finite samples and uncertain data in the estimation, the input and output variables are described as fuzzy numbers, with the metric on fuzzy number space defined. Then, the fuzzy nu-support vector machine (Fnu-SVM) is proposed on the basis of combining the fuzzy theory with the nu-support vector machine, followed by the presentation of a time estimation method based on Fnu-SVM and its relevant parameter-choosing algorithm. The results from the applications in injection mold design and software product design confirm the feasibility and validity of the estimation method. Compared with the fuzzy neural network (FNN) model, our Fnu-SVM method requires fewer samples and enjoys higher estimating precision