Fuzzy Linear Programming models and methods has been one ofthe most and well studied topics inside the broad area of Soft Computing. Itsapplications as well as practical realizations can be found in all the real worldareas. In this paper a basic introduction to the main models and methods infuzzy mathematical programming, with special emphasis on those developedby the authors, is presented. As ...

In recent years, soft computing methods, like fuzzy logic and neural networks have been  presented and developed for the purpose of mobile robot trajectory tracking. In this paper we will present a fuzzy approach to the problem of mobile robot path tracking for the CEDRA rescue robot with a complicated kinematical model. After designing the fuzzy tracking controller, the membership functions an...

Soft Computing is an interdisciplinary area that encompasses a variety of computing paradigms. Examples of some popular soft computing paradigms include fuzzy computing, neural computing, evolutionary computing, and probabilistic computing. Soft computing paradigms, in general, aim to produce computing systems/machines that exhibit some useful properties, e.g. making inference with vague and/or...

The term data mining refers to information elicitation. On the other hand, soft computing deals with information processing. If these two key properties can be combined in a constructive way, then this formation can effectively be used for knowledge discovery in large databases. Referring to this synergetic combination, the basic merits of data mining and soft computing paradigms are pointed ou...