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136
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IEEEICCI
2002
IEEE
15 years 7 months ago
Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly an...
Wiphada Wettayaprasit, Chidchanok Lursinsap, Chee-...
171
Voted
SMC
2010
IEEE
276views Control Systems» more  SMC 2010»
15 years 29 days ago
A Modified Invasive Weed Optimization Algorithm for training of feed- forward Neural Networks
— Invasive Weed Optimization Algorithm IWO) is an ecologically inspired metaheuristic that mimics the process of weeds colonization and distribution and is capable of solving mul...
Ritwik Giri, Aritra Chowdhury, Arnob Ghosh, Swagat...
244
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IWSOS
2011
Springer
14 years 5 months ago
Evolving Self-organizing Cellular Automata Based on Neural Network Genotypes
Abstract This paper depicts and evaluates an evolutionary design process for generating a complex self-organizing multicellular system based on Cellular Automata (CA). We extend th...
Wilfried Elmenreich, István Fehérv&a...
HAIS
2008
Springer
15 years 3 months ago
An Evolutionary Approach for Tuning Artificial Neural Network Parameters
The widespread use of artificial neural networks and the difficult work regarding the correct specification (tuning) of parameters for a given problem are the main aspects that mot...
Leandro M. Almeida, Teresa Bernarda Ludermir
193
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JMLR
2006
389views more  JMLR 2006»
15 years 2 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...