Shaun-Inn Wu

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<italic>We have developed a stock-market forecasting system based on artificial neural networks. The system has been trained with the Standard &amp; Poor 500 composite indexes of past twenty years. Meanwhile, the system produces the forecasts and adjusts itself by comparing its forecasts with the actual indexes. Since most of stock-market forecasting(More)
1. I n t r o d u c t i o n . R concu r ren t a lgor i thm for f ind ing the fewes t number of queens needed to "cover" the nxn chessboard, 1.~n~<8, is given here in the Modcap programming language. This algorithm is a straightforward generalization of a good serial algorithm and uses concurrency at two levels: $1MD and MIMD. The Hodcap language is well(More)
Time series models have been applied to forecast the market trends. Simple exponential smoothing (SES) method was one of them widely used as a forecasting tool in time series data. In this method, a smoothing parameter needs to be chosen in such a way tO minimize sums of squares forecast errors. By deriving the equivalence of the smoothing equation and the(More)
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