Chapter 4 - Concepts, procedures, and applications of artificial neural network models in streamflow forecasting

Abstract

Artificial neural network (ANN) model involves computations and mathematics, which simulate the human–brain processes. Many of the recently achieved advancements are related to the artificial intelligence research area such as image and voice recognition, robotics, and using ANNs. The ANN models have the specific architecture format, which is inspired by a biological nervous system. Like the structure of the human brain, the ANN models consist of neurons in a complex and nonlinear form. The neurons are connected to each other by weighted links. All the processes in ANN models, such as data collection and analysis, network structure design, number of hidden layers, network simulation, and weights/bias trade-off, are computed through learning and training methods. The ANN applications solving problems of the real world include a wide range of scientific fields from finance to hydrology and fall into the three categories: (i) pattern classification, (ii) prediction, and (iii) control and optimization. Clustering, classification, and simulation in the ANN models are performed with different kinds of structures related to the ANN models. The ANN models are categorized into three groups: (i) static ANN, (ii) dynamic ANN, and (iii) statistical ANN. Static ANN model is known as a multilayer perceptron neural network model, dynamic neural network models such as tapped delay lines and recurrent neural network models, and statistical neural network models such as radial basis function model, and generalized regression neural network model. It may also be possible to combine the ANN model with other optimization techniques, for example, adaptive neuro-fuzzy inference system for the better prediction purposes. One of the most important implications of the ANN is in hydrological systems, and this chapter provides an insight into the concept, background, theory, classification, and application of the ANN models in hydrology and water resources management.