Proportional + Integral + Derivative (PID) controllers are widely used in engineering applications such that more than half of the industrial controllers are PID controllers. There are many methods for tuning the PID parameters in the literature. In this paper an intelligent technique based on eXtended Classifier System (XCS) is presented to tune the PID controller parameters. The PID controlle...

introduction breast cancer is the second cause of mortality among women. early detection of it can enhance the chance of survival. screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. computer-aided diagnosis can help physicians make a more accurate diagnosis. materials and methods regarding the importance of separating normal and abnorm...

Genetics-based machine learning methods also called learning classifier systems are evolutionary computation based data mining techniques. The advantages of these techniques are: they are rule-based models providing human-readable learning patterns; they are incremental learners allowing the system to adapt quickly in dynamic environments; and some of them have linear 0(n) learning complexity i...

Classifier systems (CS) have proven to be useful tools for the study of genetic algorithm based learning. Unfortunately, there are a number of difficulties with the formalization that limit the representational capabilities and, hence, its problem solving abilities and the speed at which it can learn. This paper introduces VCS Variable Classifier Systems that augment the traditional CS with the...

The application of methods of machine learning is popular in Bioinformatics. Many problems in Bioinformatics can be regarded as pattern recognition problems and well-known methodologies can be used. Until now those methodologies concentrated on the use of a single genome. With the availability of datasets that contain genomes from several closely related species, information that was derived fr...

Learning Classifier Systems are a machine learning technique that may be categorised in between symbolic production systems and sub-symbolic connectionist systems. Classifiers are cognitive paradigm for adaptation that learn in environments of perpetual novelty with minimal and delayed reward. They employ two principle processes (1) reinforcement learning called ‘trial-and-error’, and genetic e...