Artificial intelligence diagnosis algorithm for expanding a precision expert forecasting system

Authors:
Chin-Tsai Lin;In-Fun Lee
Affiliations:
Graduate School of Management, Ming Chuan University, 5F, No. 130, Jihe Rd., Shihlin District, Taipei 111, Taiwan, ROC;Graduate School of Management, Ming Chuan University, 5F, No. 130, Jihe Rd., Shihlin District, Taipei 111, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

This study developed a simple and effective expert system for forecasting short-term historical and randomly fluctuating data. This study combined Grey forecasting (GM) and Markov-Fourier Grey forecasting model (MFGM) to develop an expert system of diagnosis by artificial intelligence which improves the effectiveness of forecasting randomly fluctuating data. The contribution of this study is its simple and effective artificial intelligence diagnosis algorithm approach to developing a computer environment for an expert forecasting system which accurately predicts short-term historical and stochastic volatility data.