Economic Modeling Using Artificial Intelligence Methods
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Author
Contributions
- SpringerLink (Online service) - Contributor
Publication
2013 - Imprint: Springer, London, United Kingdom
Language
English
Word Count
65,250 words, Guess
Page Count
261 pages
Physical Format
Electronic resource
Identifiers
- Internet Archiveeconomicmodeling00marw
- ISBN-139781447150107
- ISBN-101447150104
- Better World Books9781447150107
- Open LibraryOL27033852M
Classifications
- DDC006.3
- LCCQ334-342
- LCCTJ210.2-211.495
Description
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 networksradial basis functionssupport vector machinesrough setsgenetic algorithmparticle swarm optimizationsimulated annealingmulti-agent systemincremental learningfuzzy networksSignal 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.
Subjects
Topics
Series Statement
- Advanced Information and Knowledge Processing
Other Editions
- Economic Modeling Using Artificial Intelligence Methods
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