Web-based fuzzy neural networks for stock prediction

Authors:
Yu Tang;Fujun Xu;Xuhui Wan;Yan-Qing Zhang
Affiliations:
Department of Computer Science Georgia State University, Atlanta, GA;Department of Computer Science Georgia State University, Atlanta, GA;Department of Computer Science Georgia State University, Atlanta, GA;Department of Computer Science Georgia State University, Atlanta, GA
Venue:
Second international workshop on Intelligent systems design and application
Year:
2002

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Abstract

A web-based stock prediction system is developed based on a fuzzy neural network by using the past stock data to discover fuzzy rules and make future predictions. The learning algorithm is implemented. Input data to each network are the moving averages of the weekly stock data, which are obtained from http://moneycentral.msn.com. The output simulation data are also the average values of the weekly stock data. After the input data are collected from the website for the specific term using web search techniques, the system is trained and then is able to make future predictions. To implement this stock prediction System, JSP (Java Server Page), JDK1.3, JSP server and IE server 5.0 are used.