An Overview of Computational Tools

Abstract

Computational techniques is a set of bio-inspired computational methodologies and tactics to initiate complex real-world problems for which traditional simulation methods cannot be very useful. The methods are very close to the human’s way of reasoning and it is able to produce control actions in an adaptive way. This chapter explores the use of computational intelligence techniques (specifically fuzzy logic, artificial neural network and particle swarm optimization) for classification of data. The artificial intelligence mainly includes learning, reasoning, and perception used across different industries. Fuzzy logic sets enable to quantify knowledge. In ANN, the progression of the brain is used to implement algorithms that aim to develop complex design problems. Fuzzy logic is one of the disciplines in artificial intelligence which emulates human reasoning in terms of linguistic variables. There is similarity between fuzzy logic and neural networks. These methods are used to resolve problems in which any mathematical model is not involved. Systems which are implemented using combination of both fuzzy logic and neural networks are termed as neuro-fuzzy systems. These hybrid systems combine advantages of both fuzzy logic and neural networks to perform in an efficient manner.