Crossover in Genetic Programming is mostly a destructive operator, generally producing children worse than the parents and occasionally producing those who are better. A recently ...
There has been a considerable body of work on search–based test data generation for branch coverage. However, hitherto, there has been no work on multi–objective branch covera...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract. This article presents a comprehensive study of different ensemble pruning techniques applied to a bagging ensemble composed of decision stumps. Six different ensemble p...
The Louisiana Coastal Area presents an array of rich and urgent scientific problems that require new computational approaches. These problems are interconnected with common compon...