Nowadays, computational intelligence (CI) receives much attention in academic and industry due to a plethora of possible applications. CI includes fuzzy logic (FL), evolutionary algorithms (EA), expert systems (ES) and artificial neural networks (ANN). Many CI components have applications in modeling and control of dynamic systems. FL mimics the human reasoning by converting linguistic variables into a set of rules. EA are metaheuristic population-based algorithms which use evolutionary operations such as mutation, crossover, and selection to find an optimal solution for a given problem. ES are programmed based on an expert knowledge to make informed decisions in complex tasks. ANN models how the neurons are connected in animal nervous systems. ANN have learning abilities and they are trained using data to make intelligent decisions. Since ANN have universal approximation abilities, they can be used to solve regression, classification, and forecasting problems. ANNs are made of interconnected layers where every layer is made of neurons and these neurons have connections with other neurons. These layers consist of an input layer, hidden layer/layers, and an output layer.
Part of the book: Digital Systems