Intelligent systems are one of the multiaspect topics not only theoretically but also for practical reasons. The field of applications of the intelligent systems is constantly expanding, the applied methods are becoming more and more sophisticated, and many of them are synthetic. The number of investigations in the domain rapidly is growing, and this also includes a number of papers sent to us. From all these papers due to a competent cast, there were selected seven papers from Europe, Asia, Australia, and Oceania that are collected in the present special issue.
A great number of the presented papers deal with fuzzy sets. The papers of many researchers underscore the significance of the contemporary perceptionoriented methods and also of different applications in the intelligent systems. On the first place, this is valid for the paradigm of L. Zadeh "computing with words." In the above-mentioned papers, it is realized in a quite different way.
Another group of papers is more oriented toward the field of machine learning, knowledge discovery, and the treatment of uncertainty. The variety of presented ideas showed that the big changes and the impetuous development in the domain are yet to take place.
In "Improved Process Monitoring Using Nonlinear Principal Component Models," the authors D. Antory, U. Kruger, G. Irwin, and G. McCullough, (Ireland) introduced two new approaches for fast data processing. The presented elaboration surpasses the input training in all indicators, and it is much cheaper than the conventional artificial neural networks. It is widely used for complete process monitoring, involving fault detection, identification, and isolation.
The paper "Adaptive Modeling and Discovery in Bioinformatics: The Evolving Connectionist Systems Approach" by N. Kasabov (New Zealand) introduces an approach to modeling and discovering new knowledge in bioinformatics. The approach includes data training using a combination of neural networks and fuzzy logic.