Abstract

Artificial Neural Network models have helped researchers to foresee the outcome of problems in many scientific fields. These models are presumed as a computer-based stimulation of the human neural system capable to benchmark values. They employ functions among a large variety of data examples driving to knowledge, identify relationships or errors and finally provide a possible outcome. From a decisionmaking perspective the Neural Network approach is very helpful even if it is difficult to implement it in real cases. Recently they are increasingly applied in many fields of science such as finance, strategic and project management and business policy implementing forecasts, pattern recognition and predictions using historical data. This study is an overview of the basic models of Artificial Neural Networks, as much as a literature review used in specific fields of science. The goal of this study is to serve as a roadmap for an early researcher to understand the principles of Artificial Neural Network models and the underlying mathematics, to become familiar with their applications over certain areas and to guide further exploration of this area.

Keywords: Neural networks; Decision making; Finance; Science; Humans; Nucleus; Nerve