Neural-Fuzzy Systems in Stock Prices Forecasting

碩士 === 大葉大學 === 工業工程學系碩士班 === 91 === Forecasting of stock market is one of the most important topics in business. The ellipsoidal fuzzy systems learning with and without supervision has been successfully applied in control systems and pattern recognition problems. In this study, the ellipsoidal fuzz...

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Main Authors: Kuo Ping Lin, 林國平
Other Authors: Ping Feng Pai
Format: Others
Language:zh-TW
Published: 2003
Online Access:http://ndltd.ncl.edu.tw/handle/69523021564640740283
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spelling ndltd-TW-091DYU000300022015-10-13T16:56:51Z http://ndltd.ncl.edu.tw/handle/69523021564640740283 Neural-Fuzzy Systems in Stock Prices Forecasting 模糊類神經系統於股市股價預測之應用 Kuo Ping Lin 林國平 碩士 大葉大學 工業工程學系碩士班 91 Forecasting of stock market is one of the most important topics in business. The ellipsoidal fuzzy systems learning with and without supervision has been successfully applied in control systems and pattern recognition problems. In this study, the ellipsoidal fuzzy system is modified to examine the feasibility for predicting stock prices. A scale conjugate gradient learning method is borrowed to speed the training process in supervised learning. Three existing forecasting approaches are used to compare the performance. Numerical results show that the ellipsoidal fuzzy system outperforms the other three methods in forecasting stock prices. Ping Feng Pai 白炳豐 2003 學位論文 ; thesis 107 zh-TW
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language zh-TW
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description 碩士 === 大葉大學 === 工業工程學系碩士班 === 91 === Forecasting of stock market is one of the most important topics in business. The ellipsoidal fuzzy systems learning with and without supervision has been successfully applied in control systems and pattern recognition problems. In this study, the ellipsoidal fuzzy system is modified to examine the feasibility for predicting stock prices. A scale conjugate gradient learning method is borrowed to speed the training process in supervised learning. Three existing forecasting approaches are used to compare the performance. Numerical results show that the ellipsoidal fuzzy system outperforms the other three methods in forecasting stock prices.
author2 Ping Feng Pai
author_facet Ping Feng Pai
Kuo Ping Lin
林國平
author Kuo Ping Lin
林國平
spellingShingle Kuo Ping Lin
林國平
Neural-Fuzzy Systems in Stock Prices Forecasting
author_sort Kuo Ping Lin
title Neural-Fuzzy Systems in Stock Prices Forecasting
title_short Neural-Fuzzy Systems in Stock Prices Forecasting
title_full Neural-Fuzzy Systems in Stock Prices Forecasting
title_fullStr Neural-Fuzzy Systems in Stock Prices Forecasting
title_full_unstemmed Neural-Fuzzy Systems in Stock Prices Forecasting
title_sort neural-fuzzy systems in stock prices forecasting
publishDate 2003
url http://ndltd.ncl.edu.tw/handle/69523021564640740283
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