Ai and Intelligent Industrial Applications: the Rough Set Perspective

Application of intelligent methods in industry become a very challenging issue nowadays and will be of extreme importance in the future. Intelligent methods include, fuzzy sets neural networks genetics algorithms and others techniques known as soft computing. No doubt rough set theory can also contribute essentially to this domain. In this paper basic ideas of rough set theory are presented and some possible intelligent industrial applications outlined. INTRODUCTION Rough set theory is a new mathematical approach to data analysis. Basic idea of this method hinges on classification of objects of interest into similarity classes (clusters) containing objects which are indiscernible with respects to some features, e.g., colour, temperature etc., which form basic building blocks of knowledge about reality, and are employed next to find out hidden patterns in data. Basis of rough set theory can be found in Pal & Skowron (1999), Pawlak (1991), Pawlak et al., (1995) and Polkowski & Skowron (1998). Rough set theory has some overlaps with other methods of data analysis, e.g., statistics, cluster analysis, fuzzy sets, evidence theory and other but it can be viewed in its own rights as an independent discipline. The rough set approach seems to be of fundamental importance to AI and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, inductive reasoning and pattern recognition. It seems of particular importance to decision support systems and data mining. Rough set theory has been successfully applied in many real-life problems in medicine, pharmacology, engineering, banking, financial and market analysis and others. More about applications of rough set theory can be found in Lin & Cecerone (1997), Polkowski & Skowron (1998), Słowiński (1992), Szladow & Ziarko (1993), Tsumoto et al. (1996), Wang (1997) and Ziarko (1993) and others. Very promising new areas of application of the rough set concept seems to emerge in the near future. They include rough control, rough data bases, rough information retrieval, rough neural network and others. ROUGH SETS AND INTELLIGENT INDUSTRIAL APPLICATIONS Artificial intelligence approach to industrial process is real challenge for industry in the years to come. Rough set theory seems to be particularly suited for problem solving in this area. Some of them are briefly discussed below. 1) Material sciences. Application of rough sets to new materials design and investigating material properties has already shown its usefulness in this area. Pioneer work in this domain