A fitness function is needed for a Genetic Algorithm (GA) to work, and it appears natural that the combination of objectives and constraints into a single scalar function using ar...
This study develops a novel model, GA-SVR, for parameters optimization in support vector regression and implements this new model in a problem forecasting maximum electrical daily...
— A heuristic is proposed to address free parameter selection for Support Vector Machines, with the goals of improving generalization performance and providing greater insensitiv...
A fundamental problem of modelling in Systems Biology is to precisely characterise quantitative parameters, which are hard to measure experimentally. For this reason, it is common ...
Hendrik Rohn, Bashar Ibrahim, Thorsten Lenser, Tho...
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...