In diesem Aufsatz wird der Fragestellung nachgegangen, ob neuronale Netze in der Lage sind Kennzahlen für Warteschlangensysteme zu approximieren. Da für die meisten in der Praxis vorkommenden Warteschlangenprobleme keine exakten, expliziten Lösungen für die Warteschlangenkennzahlen...

In recent years, the government, of African Countries has assumed major responsibilities for economic reforms and growth. In attempting to describe their economies, economists (policymakers) in many African Countries have applied certain models that are by now widely known: Linear programming...

In the insurance business, two things are considered when analysing losses: frequency of loss and severity of loss. Previous research investigated the use of artificial Neural Networks (NNs) to develop models as aids to the insurance underwriter when determining acceptability and price on...

In this article we describe reinforcement learning, a machine learning technique for solving sequential decision problems. We describe how reinforcement learning can be combined with function approximation to get approximate solutions for problems with very large state spaces. One such problem...

Prediction is very important in business planning. The ability to accurately predict the future is fundamental to many decision activities in sales, marketing, production, inventory control, personnel, and many other functional areas of business. Time series modeling approach is one of the major...

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its...

The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced...

This paper introduces a neural-net approach to perform discriminant analysis in business research. A neural net represents a nonlinear discriminant function as a pattern of connections between its processing units. Using bank default data, the neural-net approach is compared with linear...

This note offers an extension of Tam and Kiang (Tam, K. Y., M. Y. Kiang. 1992. Management applications of neural networks: The case of bank failure predictions. Management Sci. 38(7) 926--947.). First the weakness of the standard back propagation neural network learning algorithm is discussed,...