Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/72854


Title: On Optimal Forecasting with Soft Computation for Nonlinear Time Series
Authors: Wu, Berlin
吳柏林
Chen, Shuenn-Ren
Contributors: 應數系
Keywords: optimal forecasting;soft computation;genetic modeling;membership function
Date: 2003-09
Issue Date: 2015-01-13 15:43:34 (UTC+8)
Abstract: In this paper we present a new approach on optimal forecasting by using the fuzzy set theory and soft computing methods for the dynamic data analysis. This research is based on the concepts of fuzzy membership function as well as the natural selection of evolution theory. Some discussions in the sensitivity of the design of fuzzy processing will be provided. Through the design of genetic evolution, the AIC criteria is used as the adjust function, and the fuzzy memberships function of each gene model are calculated. Simulation and empirical examples show that our proposed forecasting technique can give an optimal forecasting in time series analysis. [PUBLICATION ABSTRACT]
Relation: Fuzzy Optimization and Decision Making, 2(3), 215-228
Data Type: article
DOI 連結: http://dx.doi.org/10.1023/A:1025090420345
Appears in Collections:[應用數學系] 期刊論文

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