This paper introduces GNARL, an evolutionary program which induces recurrent neural networks that are structurally unconstrained. In contrast to constructive and destructive algor...
Gregory M. Saunders, Peter J. Angeline, Jordan B. ...
In this paper, an approach to solving the classical Traveling Salesman Problem (TSP) using a recurrent network of linear threshold (LT) neurons is proposed. It maps the classical ...
Eu Jin Teoh, Kay Chen Tan, H. J. Tang, Cheng Xiang...
— The correct segmentation and measurement of mammography images is of fundamental importance for the development of automatic or computer-aided cancer detection systems. In this...
Aida A. Ferreira, Francisco Nascimento Jr., Ing Re...
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Several recent works have used neural networks to discriminate vigilance states in humans from electroencephalographic (EEG) signals. Our study aims at being more exhaustive. It t...