Boosting the Performance of a Multiobjective Algorithm to Design RBFNNs Through Parallelization
(2007)
Presentation / Conference Contribution
Guillen, A., Rojas, I., Gonzalez, J., Pomares, H., Herrera, L. J., & Paechter, B. (2007, April). Boosting the Performance of a Multiobjective Algorithm to Design RBFNNs Through Parallelization. Presented at ICANNGA: International Conference on Adaptive and Natural Computing Algorithms, Warsaw, Poland
Radial Basis Function Neural Networks (RBFNNs) have been widely used to solve classification and regression tasks providing satisfactory results. The main issue when working with RBFNNs is how to design them because this task requires the optimizatio... Read More about Boosting the Performance of a Multiobjective Algorithm to Design RBFNNs Through Parallelization.