In this final part, we discuss fault diagnosis methods that are based on historic process
knowledge. We also compare and evaluate the various methodologies reviewed in this …

Nuclear power industries have increasing interest in using fault detection and diagnosis
(FDD) methods to improve safety, reliability, and availability of nuclear power plants (NPP) …

The capabilities of the human brain have always fascinated scientists and led them to
investigate its inner workings. Over the past 50 years a number of models have been …

Recent work on neural networks in chemistry is reviewed and essential background to this
fast-spreading method is given. Emphasis is placed on the back-propagation algorithm …

Understanding the fundamental processes of light-harvesting is crucial to the development
of clean energy materials and devices. Biological organisms have evolved complex …

Control Performance Management in Industrial Automation provides a coherent and self-
contained treatment of a group of methods and applications of burgeoning importance to the …

A Wave‐Net is an artificial neural network with one hidden layer of nodes, whose basis
functions are drawn from a family of orthonormal wavelets. The good localization …

A nonlinear internal model control (NIMC) strategy based on neural network models is
proposed for SISO processes. The neural network model is identified from input—output …

The purpose of this review is three-fold. First, sketch the directions that research and
industrial applications of “intelligent systems” have taken in several areas of process …

Fault diagnosis has been studied very actively during recent years. Estimation methods, rule-
base reasoning and pattern recognition techniques are the most common methods used to …