ABSTRACT
This chapter provides a technical overview of neural network approaches to time series prediction problems and discusses challenges associated with time series prediction and neural network solutions. It presents a general overview of time series prediction problems and traditional approaches to time series prediction. The chapter outlines neural network modeling for time series prediction and describes challenges of time series predictions and neural network solutions. It also provides a case study on an economic time series forecasting problem and demonstrates how to apply advanced neural network techniques to real-world time series prediction tasks. Artificial neural networks are statistical modeling tools that have a wide range of applications, including time series prediction. Neural networks can be applied to time series modeling without assuming a priori function forms of models. If member neural network models of a committee use the same input variables and architecture, the committee formed by these members is called a homogeneous committee.
