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Economic Modeling Using Artificial Intelligence Methods (Advanced Information and Knowledge Processing) by Tshilidzi Marwala (auth.) is a nonfiction available to read on EtoBox.

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Economic Modeling Using Artificial Intelligence Methodsexamines 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 mark

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Author

Tshilidzi Marwala (auth.)

Publisher

Springer-Verlag London

Published

2013

Language

EN

ISBN

9781447150107

Category

nonfiction

Subjects

Economics, Engineering, Mathematics