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» Introduction to artificial neural networks
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ASC
2004
13 years 8 months ago
Extracting rules from trained neural network using GA for managing E-business
Theabilitytointelligentlycollect,manageandanalyzeinformationaboutcustomersandsellersisakeysourceofcompetitive advantage for an e-business. This ability provides an opportunity to ...
Atta Ebrahim E. ElAlfi, R. Haque, M. Esmel ElAlami
AISS
2010
130views more  AISS 2010»
13 years 5 months ago
Neural Network Modeling for Proton Exchange Membrane Fuel Cell (PEMFC)
This paper presents the artificial intelligence techniques to control a proton exchange membrane fuel cell system process using particularly a methodology of dynamic neural networ...
Youssef M. ElSayed, Moataz H. Khalil, Khairia E. A...
CEC
2009
IEEE
14 years 2 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
EPS
1995
Springer
13 years 11 months ago
PANIC: A Parallel Evolutionary Rule Based System
PANIC (Parallelism And Neural networks In Classifier systems) is a parallel system to evolve behavioral strategies codified by sets of rules. It integrates several adaptive techni...
Antonella Giani, Fabrizio Baiardi, Antonina Starit...
ISNN
2010
Springer
13 years 6 months ago
MULP: A Multi-Layer Perceptron Application to Long-Term, Out-of-Sample Time Series Prediction
Abstract. A forecasting approach based on Multi-Layer Perceptron (MLP) Artificial Neural Networks (named by the authors MULP) is proposed for the NN5 111 time series long-term, out...
Eros Pasero, Giovanni Raimondo, Suela Ruffa