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Computational Intelligence in Time Series Forecasting - Theory and Engineering Applications (Hardcover, 2005 ed.) Loot Price: R4,576
Discovery Miles 45 760
Computational Intelligence in Time Series Forecasting - Theory and Engineering Applications (Hardcover, 2005 ed.): Ajoy K....

Computational Intelligence in Time Series Forecasting - Theory and Engineering Applications (Hardcover, 2005 ed.)

Ajoy K. Palit, Dobrivoje Popovic

Series: Advances in Industrial Control

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Loot Price R4,576 Discovery Miles 45 760 | Repayment Terms: R429 pm x 12*

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Foresight can be crucial in process and production control, production-and-resources planning and in management decision making generally. Although forecasting the future from accumulated historical data has become a standard and reliable method in production and financial engineering, as well as in business and management, the use of time series analysis in the on-line milieu of most industrial plants has been more problematic because of the time and computational effort required.

The advent of intelligent computational technologies such as the neural network and the genetic algorithm promotes the efficient solution of on-line forecasting problems. Their most outstanding successes include:

  • prediction of nonlinear time series and the nonlinear combination of forecasts using neural networks;
  • prediction of chaotic time series and of output data for second-order nonlinear plant using fuzzy logic.

The power of intelligent technologies applied individually and in combination, has created advanced forecasting methodologies, exemplified in Computational Intellingence in Time Series Forecasting by particular systems and processes. The authors give a comprehensive exposition of the improvements on offer in quality, model building and predictive control, and the selection of appropriate tools from the plethora available using such examples as:

  • forecasting of electrical load and of output data for nonlinear plant with neuro-fuzzy networks;
  • temperature prediction and correction in pyrometer reading, tool-wear monitoring and materials property prediction using hybrid intelligent technologies;
  • evolutionary training of neuro-fuzzy networks by the use of genetic algorithms and prediction of chaotic time series;
  • isolated use of neural networks and fuzzy logic in the nonlinear combination of traditional forecasts of temperature series obtained from a pilot-scale chemical reactor with temporarily disconnected controller.

Application-oriented engineers in process control, manufacturing, the production industries and research centres will find much to interest them in Computational Intelligence in Time Series Forecasting and the book is suitable for industrial training purposes. It will also serve as valuable reference material for experimental researchers.

General

Imprint: Springer London
Country of origin: United Kingdom
Series: Advances in Industrial Control
Release date: July 2005
First published: 2005
Authors: Ajoy K. Palit • Dobrivoje Popovic
Dimensions: 235 x 155 x 22mm (L x W x T)
Format: Hardcover
Pages: 372
Edition: 2005 ed.
ISBN-13: 978-1-85233-948-7
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 1-85233-948-9
Barcode: 9781852339487

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