In this paper, a hybrid medical image segmentation approach is proposed based on a dual front evolution and fast sweeping evolution. This approach is composed of two stages. In th...
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Abstract- Choosing the best parameter setting is a wellknown important and challenging task in Evolutionary Algorithms (EAs). As one of the earliest parameter tuning techniques, th...
The aim of developing an agent that is able to adapt its actions in response to their effectiveness within the game provides the basis for the research presented in this paper. It ...
Hybrid set of optimally trained feed-forward, Hopfield and Elman neural networks were used as computational tools and were applied to immunoinformatics. These neural networks ena...