Computational Intelligence in Data-Driven Modelling and Its Engineering Applications
Computational Intelligence in Data-Driven Modelling and Its Engineering Applications is a scholarly work, published in 2018 in ''Mathematical Problems in Engineering''. The main subjects of the publication include data mining, artificial intelligence, complex system, artificial neural network, computational intelligence, fault detection and isolation, statistical inference, machine learning, and computer science. Modern engineering systems show increasing complexity due to their high nonlinearity and large disturbances and uncertainties introduced into the systems.In many circumstances, the conventional mathematical models that can accurately describe these complex systems and can be exploited in reallife applications, such as differential equations or statistical models, do not exist.However, with the fast development of advanced sensing, measurement, and data collection technologies, large amounts of data that represent input-output relationships of the systems become available.This makes data-driven modelling (DDM) possible and practical.Data-driven modelling aims at information extraction from data and is normally used to elicit numerical predictive models with good generalisation ability, which can be viewed as regression problems in mathematics.It analyses the data that characterise a system to find relationships among system state variables (input, internal, and output variables) without taking into account explicit knowledge about physical behaviours.Many paradigms utilised in DDM have been established based on statistics and/or computational intelligence.For instance, artificial neural networks (ANNs) and fuzzy rule-based systems (FRBSs) serve as fundamental model frameworks, which are alternatives to statistical inference methods.Evolutionary algorithms (EAs), swarm intelligence (SI), and machine learning (ML) methods provide learning and optimisation abilities for calibrating and improving the intelligent or statistical models.In recent years, DDM has found widespread applications, ranging across machinery manufacturing, materials processing, power and energy systems, transport, and so forth.