STATISTICAL LEARNING NETWORKS IN SIMULATIONS FOR BUSINESS TRAINING AND EDUCATION
Palabras clave:
Business Simulations, Artificial Neural Networks, Deep Neural Networks, Statistical Learning Networks, Multi-Layered Networks of Active Neurons, Group Method of Data HandlingResumen
Statistical Learning Networks can address the common problems of Artificial Neural Networks (ANNs) such as: difficulties in interpretation of the results, the problem of overfitting, designing ANNs topology is in general a trial-and-error process and there are no rules for using the theoretical a priori knowledge in ANNs design. This paper discusses a highly automated procedure for developing Statistical Learning Networks in the form of Multi-Layered Networks of Active Neurons (MLNAN) for business simulations using the Group Method of Data Handling. MLNAN helps researchers by making business simulations development more cost-effective. All results so far show that MLNAN is able to develop reliable complex models with better overall error rates than state-of-the-art methods. This paper presents some of the results from international research done in Europe, Australia, and the United States.
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