Title
Neural, Novel & Hybrid Algorithms for Time Series Prediction,New
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An authoritative guide to predicting the future using neural, novel, and hybrid algorithmsExpert Timothy Masters provides you with carefully paced, stepbystep 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 SavitzkyGolay filters for suggesting and validating prediction models* Effective preprocessing techniques for prediction with neural networksCDROM INCLUDES:* PREDICTboth DOS and Windows NT versionsa powerful time series program that can be easily customized to make accurate predictions in any application area* Much useful source code, including the complexgeneral multivariate fast Fourier transform in both C++ and Pentiumoptimized assembler
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To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What topics are covered in 'Neural, Novel & Hybrid Algorithms for Time Series Prediction'? A: The book covers various topics including robust confidence intervals, wavelets for feature detection, multivariate ARMA models, hybrid ARMA/neural models, data reduction techniques, digital filters for preprocessing, and diagnostic tools for validating prediction models.
- Q: Who is the author of this book? A: The author of 'Neural, Novel & Hybrid Algorithms for Time Series Prediction' is Timothy Masters.
- Q: When was this book published? A: This book was published on October 20, 1995.
- Q: What format is the book available in? A: The book is available in paperback binding.
- Q: How many pages does the book have? A: The book contains a total of 514 pages.
- Q: Is there any software included with the book? A: Yes, the book includes a CD-ROM that contains a powerful time series program called PREDICT, which is available for both DOS and Windows NT.
- Q: What condition is the book in? A: The book is listed as being in good condition.
- Q: What are some applications of the techniques discussed in the book? A: The techniques discussed in the book can be applied to business forecasting, stock market prediction, engineering process control, economic cycle tracking, and marketing analysis.
- Q: Are there any special features included in the book? A: The book provides effective preprocessing techniques for neural networks and includes much useful source code related to multivariate fast Fourier transforms.
- Q: Can beginners understand the content of this book? A: The book is designed to provide step-by-step advice, making it accessible for readers who may be new to the concepts of neural and hybrid algorithms for time series prediction.