C++ Neural Networks and Fuzzy Logic: Preface

C++ Neural Networks and Fuzzy Logic

by Valluru B. Rao

MTBooks, IDG Books Worldwide, Inc.

ISBN: 1558515526   Pub Date: 06/01/95

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The stability and robustness of this system was checked by using over 1000 moving time windows of

3−month, 6−month, and 12−month duration over the 4.5−year interval and noting the standard deviations in

profits and maximum drawdown. The maximum drawdown varied from 30 to 48 basis points.

Neural Nets versus Box−Jenkins Time−Series Forecasting

Ramesh Sharda and Rajendra Patil used a standard 12−12−1 feedforward backpropagation network and

compared the results with Box−Jenkins methodology for time−series forecasting. Box−Jenkins forecasting is

traditional time−series forecasting technique. The authors used 75 different time series for evaluation. The

results showed that neural networks achieved better MAPE (mean absolute percentage error) with a mean

over all 75 time series MAPEs of 14.67 versus 15.94 for the Box−Jenkins approach.