The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians..
Offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation..
The application of intelligent systems has been found useful in problems when the process is either difficult to model or difficult to solve by conventional methods. Intelligent systems have attracted increasing attention in recent years for solving many complex problems. Computational Intelligence in Control will be a repository for the theory and applications of intelligent systems techniques in modelling control and automation..
