Neural, Novel & Hybrid Algorithms for Time Series Prediction [Paperback]

Timothy Masters (Author)

Book Description

ISBN-10: 0471130419 | ISBN-13: 978-0471130413 | Publication Date: October 6, 1995

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

Editorial Reviews

From the Publisher

Covering both the practical application of traditional prediction methods and Master's own innovative techniques featuring neural and fuzzy algorithms, this outstanding guide provides concepts, approaches, and implementation plus software and tools that will aid readers in not only developing successful applications but in selecting the right methods for a variety of problems. Each subject is treated in an intuitive manner, appealing to the reader's common sense and experience. The mathematical foundations of the subject are rigorously summarized with references to additional advanced sources supplied as needed. Complete C++ source code illustrates practical implementation details and, for more important or obscure techniques, actual data is used in example applications.

From the Back Cover

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

See all Editorial Reviews

Product Details

• Paperback: 514 pages
• Publisher: John Wiley & Sons (October 6, 1995)
• Language: English
• ISBN-10: 0471130419
• ISBN-13: 978-0471130413
• Product Dimensions: 9.2 x 7.5 x 1.2 inches
• Shipping Weight: 2 pounds
• Average Customer Review: 3.0 out of 5 stars  See all reviews (8 customer reviews)
• Amazon Best Sellers Rank: #340,882 in Books (See Top 100 in Books)
  • #37 in Books > Computers & Technology > Computer Science > Artificial Intelligence > Neural Networks

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Customer Reviews

Most Helpful Customer Reviews

6 of 6 people found the following review helpful:

3.0 out of 5 stars Not for beginners, October 27, 2001

By 

Dr. Lee D. Carlson (Baltimore, Maryland USA) - See all my reviews
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This review is from: Neural, Novel & Hybrid Algorithms for Time Series Prediction (Paperback)

Prediction methods for time series are a multi-million dollar industry and are of upmost importance in financial engineering, weather prediction, logistics, network modeling, and myriads of other fields. This book gives an overview of various methodologies for time series prediction, and is written for readers with substantial experience in this area. The author emphasizes that time series prediction is more of an art rather than a science, with the practitioner usually employing hybrids of established techniques, only some of which have a rigorous mathematical foundation. In fact, despite the subject matter, this book is very lean on mathematics, and the reader will have to consult other books for a more detailed mathematical treatment. The NPredict package accompanying the book is designed to run on an NT and a DOS platform, and illustrates the main points in the book. Readers who have familiarity with the authors earlier books on neural networks will definitely find this one easier to follow. It is, again, not written for beginning students, but the author does a fairly good job of presenting the material for the advanced reader.

8 of 9 people found the following review helpful:

5.0 out of 5 stars Excellent work, July 15, 2003

By 

George Apostol (Keasbey, NJ United States) - See all my reviews

This review is from: Neural, Novel & Hybrid Algorithms for Time Series Prediction (Paperback)

I usually don't pay attention to readers's comments or reviews.
Because after all this is a very subjective matter. I bought the book for two reasons neither of which has to do with a reader's review. The first reason was because I have a copy of Timothy's book on Practical Neural Networks in C++, which I found excellent, and the second reason was because I had previewed chapter one before I bought the book and liked it very much for what it had to say and the way it said it. Timothy's books are for a wide audience of intelligent people, not necessarily all rocket scientists, and although a mathematician himself, restricts math as much as possible so people do not get bogged down by the math and loose the forest for the trees. On the other hand there is sufficient amount of bibliography for any one who is interested to pursue most rigorous or more exotic approaches. The code examples are good and the executable file NPREDICT, works without any further processing, for those who don't want to mess with code and compiling. The treatment of Box-Jekins ARMA model,and the multivariate example on temperature and precipitation is very good. The book is highly recomended to any one who has little or no knowledge of the subject, and wants to understand what time series is all about

5 of 6 people found the following review helpful:

5.0 out of 5 stars Excellant Book on Time-Series forecasting!, March 28, 1998

By 

[e-mail] (Denver, Colorado) - See all my reviews

This review is from: Neural, Novel & Hybrid Algorithms for Time Series Prediction (Paperback)

An excellant practical, hands-on book for filtering, pre-processing data for forecasting using ARMA, NN and combination of both systems. It contains a lot of background tools to do the job. NN discusstion was short since I would like to see more discussion on the different network types (but you might check his other NN with C++ books). The book also discusses confidence intervals with ARMA and NN. The majority of the book is on filtering, pre-processing etc... It just depends on what type of book you are looking for. The description contains an error. The book doesnt contain any FUZZY techniques. Masters is an excellant author.