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PPSN
1990
Springer
14 years 1 months ago
Feature Construction for Back-Propagation
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Selwyn Piramuthu
CEC
2007
IEEE
14 years 3 months ago
Combine and compare evolutionary robotics and reinforcement Learning as methods of designing autonomous robots
—The purpose of this paper is to present a comparison between two methods of building adaptive controllers for robots. In spite of the wide range of techniques which are used for...
Sergiu Goschin, Eduard Franti, Monica Dascalu, San...
IWANN
2007
Springer
14 years 3 months ago
A Novel 2-D Model Approach for the Prediction of Hourly Solar Radiation
In this work, a two-dimensional (2-D) representation of the hourly solar radiation data is proposed. The model enables accurate forecasting using image prediction methods. One year...
Fatih Onur Hocaoglu, Ömer Nezih Gerek, Mehmet...
IJCNN
2006
IEEE
14 years 3 months ago
An Adaptive Penalty-Based Learning Extension for Backpropagation and its Variants
Abstract— Over the years, many improvements and refinements of the backpropagation learning algorithm have been reported. In this paper, a new adaptive penalty-based learning ex...
Boris Jansen, Kenji Nakayama
NN
2002
Springer
13 years 8 months ago
Self-organizing maps with recursive neighborhood adaptation
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to multivariate data analysis. In that context, this paper presents variants of the...
John Aldo Lee, Michel Verleysen