MARTÍNEZ ESTUDILLO, FRANCISCO JOSÉ, Hervás-Martínez C. , TORRES JIMÉNEZ, MERCEDES, MARTÍNEZ ESTUDILLO, ALFONSO CARLOS
No
Rev. Metodos Cuantitativos Econ. Empresa
Article
Científica
0.114
01/01/2007
2-s2.0-38749146482
The main aim of this work is to show a neural network model called product unit neural network (PUNN), which is a non-linear model to solve classification problems. We propose an evolutionary algorithm to simultaneously design the topology of the network and estimate its corresponding weights. The methodology proposed combines a non-linear model and an evolutionary algorithm and it is applied to solve a real economic problem that occurs in the financial management. To evaluate the performance of the classification models obtained, we compare our approach with several classic statistical techniques such us logistic regression and linear discriminat analysis, and with the multilayer perceptron neural network model based on sigmoidal units trained by means of Back-Propagation algorithm (MLPBP).
Classification; Evolutionary neural networks; Product unit neural networks