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Economic modeling using artificial intelligence methods

Author: Tshilidzi Marwala
Publisher: London : Springer, [2013] ©2013
Series: Advanced information and knowledge processing.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

This book examines the application of artificial intelligence methods to model economic data. It addresses causality and proposes new frameworks for dealing with this issue. It also applies  Read more...

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Additional Physical Format: Electronic version:
Marwala, Tshilidzi, 1971-
Economic modeling using artificial intelligence methods.
London ; New York : Springer, ©2013
(OCoLC)839430769
Document Type: Book
All Authors / Contributors: Tshilidzi Marwala
ISBN: 9781447150091 1447150090
OCLC Number: 825754128
Description: xvi, 261 pages : illustrations ; 25 cm.
Contents: Introduction to Economic Modeling --
Techniques for Economic Modeling: Unlocking the Character of Data --
Automatic Relevance Determination in Economic Modeling --
Neural Approaches to Economic Modeling --
Bayesian Support Vector Machines for Economic Modeling: Application to Option Pricing --
Rough Sets Approach to Economic Modeling: Unlocking Knowledge in Financial Data --
Missing Data Approaches to Economic Modeling: Optimization Approach --
Correlations Versus Causality Approaches to Economic Modeling --
Evolutionary Approaches to Computational Economics: Application to Portfolio Optimization --
Real-Time Approaches to Computational Economics: Self Adaptive Economic Systems --
Multi-agent Approaches to Economic Modeling: Game Theory, Ensembles, Evolution and the Stock Market --
Control Approaches to Economic Modeling: Application to Inflation Targeting --
Modeling Interstate Conflict: The Role of Economic Interdependency for Maintaining Peace --
Conclusions and Further Work.
Series Title: Advanced information and knowledge processing.
Responsibility: Tshilidzi Marwala.

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From the reviews:"The book explores the application of artificial intelligence methods to economic data modelling. ... the book is well addressed to graduate students as well as researchers and Read more...

 
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