Economic modeling using artificial intelligence methods

Resource Information

The work Economic modeling using artificial intelligence methods represents a distinct intellectual or artistic creation found in University of Missouri Libraries. This resource is a combination of several types including: Work, Language Material, Books.

Label

Economic modeling using artificial intelligence methods

Statement of responsibility

Tshilidzi Marwala

Creator

• Marwala, Tshilidzi, 1971-

Subject

• Artificial intelligence
• Artificial intelligence
• Artificial intelligence
• Artificial intelligence.
• BUSINESS & ECONOMICS -- Economics | Theory
• Computational Intelligence.
• Computational Science and Engineering.
• Computer Simulation
• Computer science.
• Economics -- Computer simulation
• Economics -- Computer simulation
• Economics -- Computer simulation
• Economics -- Data processing
• Economics -- Data processing
• Economics -- Data processing
• Economics, Mathematical.
• Edonomics
• Electronic Data Processing
• Electronic books
• Electronic bookss
• Game Theory/Mathematical Methods.
• Mathematical statistics.
• Optical pattern recognition.
• Pattern Recognition.
• Artificial Intelligence

Language

eng

Summary

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

Member of

• Advanced information and knowledge processing

Cataloging source

GW5XE

Dewey number

330.01/13

Illustrations

illustrations

Index

index present

Language note

English

LC call number

HB143.5

LC item number

.M37 2013

Literary form

non fiction

Nature of contents

• dictionaries
• bibliography

NLM call number

HB 143.5

Series statement

Advanced information and knowledge processing,