Economic Modeling Using Artificial Intelligence Methods (Record no. 57573)

000 -LEADER
fixed length control field 05033nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-1-4471-5010-7
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112224.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130403s2013 xxk| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781447150107
-- 978-1-4471-5010-7
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Marwala, Tshilidzi.
245 10 - TITLE STATEMENT
Title Economic Modeling Using Artificial Intelligence Methods
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVI, 261 p.
490 1# - SERIES STATEMENT
Series statement Advanced Information and Knowledge Processing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Foreword -- Preface -- Acknowledgements -- 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 -- Index.
520 ## - SUMMARY, ETC.
Summary, etc Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace - and vice versa - is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4471-5010-7
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- London :
-- Springer London :
-- Imprint: Springer,
-- 2013.
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-- text
-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern recognition.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer mathematics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Economic theory.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Economic Theory/Quantitative Economics/Mathematical Methods.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Science and Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern Recognition.
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-- Statistics and Computing/Statistics Programs.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1610-3947
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