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...

Artificial neural networks, which simulate neuronal systems of the brain, are useful methods that have attracted the attention of researchers in many disciplinary areas. They have many advantages over traditional methods in situations where the input-output relationship of the system under study...

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...

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...

You do not have to look far and we can see that every electronic device is built around at least one processor which is a miniature brain, in the most simplified way (borrows a few features that help to control that device). Scientists try to simulate a brain to fully comply with the biological...

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...

The frequency of construction litigation has increased over the years, making litigation a costly and time-consuming activity. It is in the interests of all parties to a construction contract to avoid litigation. A tool (Ant Miner) is proposed to predict the outcome of construction litigation,...

This paper addresses how neural networks learn to play one-shot normal form games through experience in an environment of randomly generated game payoffs and randomly selected opponents. This agent based computational approach allows the modeling of learning all strategic types of normal form...