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SMC
2010
IEEE
276views Control Systems» more  SMC 2010»
13 years 7 months 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...
IJCNN
2006
IEEE
14 years 2 months ago
Effective Training Methods for Function Localization Neural Networks
— Inspired by Hebb’s cell assembly theory about how the brain worked, we have developed a function localization neural network (FLNN). The main part of a FLNN is structurally t...
Takafumi Sasakawa, Jinglu Hu, Katsunori Isono, Kot...
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
14 years 2 months ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon
GECCO
2003
Springer
14 years 1 months ago
Pruning Neural Networks with Distribution Estimation Algorithms
Abstract. This paper describes the application of four evolutionary algorithms to the pruning of neural networks used in classification problems. Besides of a simple genetic algor...
Erick Cantú-Paz
IJCNN
2008
IEEE
14 years 2 months ago
Numerical condition of feedforward networks with opposite transfer functions
— Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfe...
Mario Ventresca, Hamid R. Tizhoosh