Intelligent Techniques for Data Modeling Problems : Nature inspired meta-heuristics and learning models applied to time series modeling and forecasting

Language: English

Published by LAP Lambert Academic Publishing, 2012

3848434792 / 9783848434794

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nach der Bestellung gedruckt Neuware - Printed after ordering - Supervised learning deals with the problem of discovering models from data as relationships between input and output attributes. Two types of models are distinguished: regression models (for continuous output attributes) and classification models (for discrete output attributes). This thesis addresses both regression and classification problems with an emphasis on new applications and on presenting improved evolutionary techniques. Such techniques include Gene Expression Programming (classical and its adaptive version), Genetic Programming, and the hypernetwork model of learning (classical and its evolutionary version). Such methods can be successfully applied to many problems from various domains. This thesis presents applications for symbolic regression for inverse problems, quantum circuit design, modeling of dynamic processes, and forecasting price movement.

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Title
Intelligent Techniques for Data Modeling Problems : Nature inspired meta-heuristics and learning models applied to time series modeling and forecasting
Author
Elena B utu
Publisher
LAP Lambert Academic Publishing
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3848434792
ISBN 13
9783848434794
Item weight
350 grams
Dimensions
220x176x33 mm

AHA-BUCH GmbH

Einbeck, Germany

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