We present and evaluate a method for estimating the relevance and calibrating the values of parameters of an evolutionary algorithm. The method provides an information theoretic m...
In this paper, we introduce an adaptive evolutionary approach to solve the short-term electrical generation scheduling problem (STEGS). The STEGS is a hard constraint satisfaction...
The aim of this paper is to study the use of Evolutionary Multiobjective Techniques to improve the performance of Neural Networks (NN). In particular, we will focus on classificati...
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...
This paper introduces a novel method of visual learning based on Genetic Programming, which evolves a population of individuals (image analysis programs) that process attributed v...