Peak ground acceleration prediction by artificial neural networks for Northwestern Turkey.
Günaydın, Kemal, Günaydın, Ayten (2008)
Mathematical Problems in Engineering
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Günaydın, Kemal, Günaydın, Ayten (2008)
Mathematical Problems in Engineering
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Izabela Rojek (2010)
Control and Cybernetics
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Do Hoai, Nam, Udo, Keiko, Mano, Akira (2011)
Journal of Applied Mathematics
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Eraslan, Ergün (2009)
Mathematical Problems in Engineering
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Matteo Matteucci, Dario Spadoni (2004)
International Journal of Applied Mathematics and Computer Science
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In this paper we focus on the problem of using a genetic algorithm for model selection within a Bayesian framework. We propose to reduce the model selection problem to a search problem solved using evolutionary computation to explore a posterior distribution over the model space. As a case study, we introduce ELeaRNT (Evolutionary Learning of Rich Neural Network Topologies), a genetic algorithm which evolves a particular class of models, namely, Rich Neural Networks (RNN), in order to...
S. Monira Sumi, M. Faisal Zaman, Hideo Hirose (2012)
International Journal of Applied Mathematics and Computer Science
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In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid...
Jadranka Jović (1997)
The Yugoslav Journal of Operations Research
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D. Zhang, Q. Jiang, X. Li (2005)
Mathware and Soft Computing
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This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. The forecasting...
Andreou, A.S., Zombanakis, G.A., Georgopoulus, E.F., Likothanassis, S.D. (2000)
Discrete Dynamics in Nature and Society
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Acevedo, María Elena, Acevedo, Marco Antonio, Felipe, Federico (2009)
Mathematical Problems in Engineering
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