Neural networks deviate from other models by their ability to map inputs to the outputs and build complex relationships among variables without specifying them explicitly. In this work we provide an extensive literature survey of the related problems and study several approaches, including conventional predictive methods. As a result of our analysis we propose two new methods, the multi-context recurrent networks and the hybrid networks, i.e., the auto-regressive multi-context recurrent neural networks. We consider them in context of the forecasting system design and development. We developed...

This book explains the principles of different types of Neural Networks such as Feed Forward, Cascade Feed Forward and Radial Basis Function Neural Networks. It also describes Fuzzy Logic concepts and Membership Functions. It is needed to mention that Neuron-Fuzzy Inference systems are come from Fuzzy Logic and Neural Network concepts; these are adaptive techniques that are given in detail in this book. Support Vector Machines are presented here as well. Applications such as direct current motors, student administration system, and electrical faults are employed to implement the above soft...