By Shu-Heng Chen
Chen, Jain, and Tai compile a number of attention-grabbing purposes of computational intelligence ways of their edited Computational Economics: A point of view from Computational Intelligence e-book. Contributions during this quantity exhibit how combos of neural networks, genetic algorithms, wavelets, fuzzy units, and agent-based modeling are used in fixing a bunch of managerial decision-making difficulties. the quantity is wealthy with functions in monetary modeling, alternative pricing, market-making, optimization of marketplace techniques, optimization for site visitors coverage, price estimation, coverage appraisal in a felony justice process, capital keep an eye on, and fixing association concept difficulties.
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Extra info for Computational Economics: A Perspective from Computational Intelligence
Paper presented at the 9th International Conference on Computing in Economics and Finance, University of Washington, Seattle, July. -H. (2001a). Evolving traders and the faculty of the business school: A new architecture of the artificial stock market. Journal of Economic Dynamics and Control, 25, 363-393. -H. (2001b). Toward an integration of social learning and individual learning in agent-based computational stock markets: The approach based on population genetic programming. Journal of Management and Economics, 5(5).
The discriminate functions can take any shape, as required by the input data clusters. In terms of the mapping abilities, the MLP with a (nonpolynomial) Tauber-Wiener transfer function is believed to be a universal approximator. For three layers MLP used in this chapter for prediction and strategy development a one-period price forecast takes the following form: Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
2001a). Evolving traders and the faculty of the business school: A new architecture of the artificial stock market. Journal of Economic Dynamics and Control, 25, 363-393. -H. (2001b). Toward an integration of social learning and individual learning in agent-based computational stock markets: The approach based on population genetic programming. Journal of Management and Economics, 5(5). , & Chen, H. (1995). Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems.
Computational Economics: A Perspective from Computational Intelligence by Shu-Heng Chen