Artificial Neural Networks (ANNs) are being used increasingly to predict and forecast water
resources variables. In this paper, the steps that should be followed in the development of …

A fuzzy logic system (FLS) is unique in that it is able to simultaneously handle numerical
data and linguistic knowledge. It is a nonlinear mapping of an input data (feature) vector into …

Deep neural networks are powerful tools in learning sophisticated but fixed mapping rules
between inputs and outputs, thereby limiting their application in more complex and dynamic …

Designed as an introductory level textbook on Artificial Neural Networks at the postgraduate
and senior undergraduate levels in any branch of engineering, this self-contained and well …

Artificial neural networks possess several properties that make them particularly attractive for
applications to modelling and control of complex non-linear systems. Among these …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

The goal of continual learning is to find a model that solves multiple learning tasks which are
presented sequentially to the learner. A key challenge in this setting is that the learner may" …

It has been observed by many authors that the backpropagation (BP) error surfaces usually
consist of a large amount of flat regions as well as extremely steep regions. As such, the BP …

The single-layer perceptron, introduced by Rosenblatt in 1958, is one of the earliest and
simplest neural network models. However, it is incapable of classifying linearly inseparable …

Very short-term load forecasting predicts the loads in electric power system one hour into the
future in 5-min steps in a moving window manner. To quantify forecasting accuracy in real …