Neural, Novel and Hybrid Algorithms for Time Series Prediction

Overview

An authoritative guide to predicting the future using neural, novel, and hybrid algorithms

Expert Timothy Masters provides you with carefully paced, step-by-step advice and guidance plus the proven tools and techniques you need to develop successful applications for business forecasting, stock market prediction, engineering process control, economic cycle tracking, marketing analysis, and more. Neural, Novel & Hybrid Algorithms for Time ...

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1995 This is an ex-library book and may have the usual library/used-book markings inside. This book has soft covers. In fair condition, suitable as a study copy., 1100grams, ... ISBN: 9780471130413. *****PLEASE NOTE: This item is shipping from an authorized seller in Europe. In the event that a return is necessary, you will be able to return your item within the US. To learn more about our European sellers and policies see the BookQuest FAQ section***** Read more Show Less

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Overview

An authoritative guide to predicting the future using neural, novel, and hybrid algorithms

Expert Timothy Masters provides you with carefully paced, step-by-step advice and guidance plus the proven tools and techniques you need to develop successful applications for business forecasting, stock market prediction, engineering process control, economic cycle tracking, marketing analysis, and more. Neural, Novel & Hybrid Algorithms for Time Series Prediction provides information on:
* Robust confidence intervals for predictions made with neural, ARIMA, and other models
* Wavelets for detecting features that presage important events
* Multivariate ARMA models for simultaneous prediction of multiple series based on multiple inputs and shocks
* Hybrid ARMA/neural models to improve the accuracy of predictions
* Data reduction and orthogonalization using principal components and related operations
* Digital filters for preprocessing to enhance useful information and suppress noise
* Diagnostic tools such as the maximum entropy spectrum and Savitzky-Golay filters for suggesting and validating prediction models
* Effective preprocessing techniques for prediction with neural networks

CD-ROM INCLUDES:
* PREDICT-both DOS and Windows NT versions-a powerful time series program that can be easily customized to make accurate predictions in any application area
* Much useful source code, including the complex-general multivariate fast Fourier transform in both C++ and Pentium-optimized assembler

Covering both the practical application of traditional prediction methods and Masters' own techniques featuring neural and fuzzy algorithms, this book provides concepts, methods, and implementation in one volume, plus software and tools that will aid the developer not only in developing successful applications, but in choosing the right approaches to a variety of problems.

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Product Details

  • ISBN-13: 9780471130413
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 10/6/1995
  • Edition description: BK&CD-ROM
  • Edition number: 1
  • Pages: 544
  • Product dimensions: 7.50 (w) x 9.24 (h) x 1.24 (d)

Meet the Author

TIMOTHY MASTERS received his PhD in mathematics in 1981. Since then he has worked as a consultant to the defense community and to industry. He is the author of Practical Neural Network Recipes in C++; Signal and Image Processing with Neural Networks: A C++ Sourcebook and Advanced Algorithms for Neural Networks: A C++ Sourcebook. His current research focuses on high-level image understanding using artificial intelligence and neural networks.
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Table of Contents

Preprocessing.

Subduing Seasonal Components.

Frequency-Domain Techniques I: Introduction.

Frequency-Domain Techniques II: Filters and Features.

Wavelet and QMF Features.

Box-Jenkins ARMA Models.

Differencing.

Robust Confidence Intervals.

Numerical and Statistical Tools.

Neural Network Tools.

Using the NPREDICT Program.

Appendices.

Bibliography.

Index.

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