By Raymond Chiong
Lately, nature has influenced many profitable options, algorithms, and computational functions permitting conventionally tricky difficulties to be solved via novel computing platforms.
Nature-Inspired Informatics for clever purposes and data Discovery: Implications in company, technological know-how, and Engineering presents the newest findings in nature-inspired algorithms and their purposes for breakthroughs in quite a lot of disciplinary fields. This defining reference assortment comprises chapters written by way of best researchers and famous academicians in the box, supplying readers a beneficial and enriched accumulation of data.
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Additional resources for Nature-inspired informatics for intelligent applications and knowledge discovery: implications in business, science, and engineering
This chapter proposes the use of a genetic program (GP) to predict future foreign exchange rates. The GP is an extension of the DyFor GP tailored for forecasting in dynamic environments. The GP is tested on the Australian / US (AUD/USD) exchange rate and compared against a basic economic model. The results show that the system has potential in forecasting long term values, and may do so better than established models. Further improvements are also suggested. ch002 Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
3599-3603), Dalian, China. , & Nakanishi, Y. (2000). A particle swarm optimization for reactive power and voltagecontrol considering voltage security assessment. IEEE Transactions on Power Systems, 15(4), 1232–1239. , Lai, K. , & Wang, S. Y. (2008). An evolutionary programming based knowledge ensemble model for business risk identification. ), Soft computing applications in business (pp. 57-72). Studies in Fuzziness and Soft Computing 230, Berlin: Springer Verlag. Yuan, X. , Yuan, Y. , & Zhang, X.
N. (2007). Fundamentals of natural computing: An overview. Physics of Life Reviews, 4(1), 1–36. 002 de Vega, F. , Roa, L. , & Sanchez, J. M. (2000). Medical knowledge representation by means of multipopulation genetic programming: An application to burn diagnosing. In Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 619-622), Chicago, IL, USA. Dorigo, M. (1992). Optimization, learning and natural algorithms. Doctoral thesis, Politecnico di Milano, Italy.