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Abstract: this paper, we attempt to compare the performance of hybrid soft computing and hard computing techniques to predict the average monthly forex rates one month ahead. The soft computing models considered are a neural network trained by the scaled conjugate gradient algorithm and a neuro-fuzzy model implementing a multi-output Takagi-Sugeno fuzzy inference system. We also considered Multivariate Adaptive Regression Splines (MARS), Classification and Regression Trees (CART) and a hybrid CART-MARS... (Update)
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BibTeX entry: (Update)
@misc{ and-unknown,
author = "Hybrid Soft And",
title = "Unknown",
url = "citeseer.ist.psu.edu/734553.html" }
Citations (may not include all citations):273 Multivariate Adaptive Regression Splines (context) - Friedman - 1991
56 A Scaled Conjugate Gradient Algorithm for Fast Supervised Le.. (context) - Moller - 1993
48 Neuro-Fuzzy and Soft Computing: A Computational Approach to .. (context) - Jang, Sun et al. - 1997
30 Chapman and Hall (context) - Breiman, Friedman et al. - 1984
22 Roles of Soft Computing and Fuzzy Logic in the Conception (context) - Zadeh - 1998
20 Neuro-Fuzzy Systems: State-of-the-Art Modeling Techniques - Abraham - 2084
5 International Financial Markets (context) - Grabbe - 1996
4 CART: Tree-Structured Nonparametric Data Analysis (context) - Steinberg, Colla - 1995
3 An Intelligent Forex Monitoring System (context) - Abraham, Chowdhury - 2001
3 MARS: Still an Alien Planet in Soft Computing (context) - Abraham, Steinberg - 2001
2 Analysis of Hybrid Soft and Hard Computing Techniques for Fo.. - Abraham - 2002
2 Australian Forex Market Analysis Using Connectionist Models - Abraham, Chowdury et al. - 2003
2 Electronic Currency Trading for Maximum Profit (context) - Longl, Walter - 2001
2 Macmillan Press (context) - Dormale, of - 1997
1 Salford Systems Inc (context) - Steinberg, Colla et al. - 1999
1 Introduction to Forex Market (context) - Forex - 2004
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