Mihail Motzev


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.


Business Simulations, Artificial Neural Networks, Deep Neural Networks, Statistical Learning Networks, Multi-Layered Networks of Active Neurons, Group Method of Data Handling

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