Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory Book

Preface; Z. Pawlak. Scope and Goals of the Book; R. Slowinski. Part I: Applications of the Rough Sets Approach to Intelligent Decision Support. 1. LERS — A System for Learning from Examples Based on Rough Sets; J.W. Grzymala-Busse. 2. Rough Sets in Computer Implemetation of Rule-Based Control of Industrial Process; A. Mrózek. 3. Analysis of Diagnostic Symptoms in Vibroacoustic Diagnostic by Means of the Rough Sets Theory; R. Nowicki, R. Slowinski, J. Stefanowski. 4. Knowledge-Based Process Control Using Rough Sets; A.J. Szladown, W.P. Ziarko. 5. Acquisition of Control Algorithms from Operation Data; W.P. Ziarko. 6. Rough Classification of HSV Patients; K. Slowinski. 7. Surgical Wound Infection — Conducive Factors and their Mutual Dependencies; M. Kandulski, J. Marciniec, K. Tukallo. 8. Fuzzy Inference System Based on Rough Sets and its Application to Medical Diagnosis; H. Tanaka, H. Ishibuchi, T. Shigenaga. 9. Analysis of Structure-Activity Relationships of Quaternary Ammonium Compounds; J. Krysinski. 10. Rough Sets-Based Study of Voter Preference in 1988 U.S.A. Presidential Election; M. Hadjimichale, A. Wasilewska. 11. An Application of Rough Set Theory in the Control of Water Conditions in a Polder; A. Reinhard, B. Stawski, T. Weber, U. Wybraniec-Skardowska. 12. Use of 'Rough Sets' Methods to draw Premonitory Factors for Earthquakes by emphasising Gas Geochemistry: The Case of a Low Seismic Activity Context in Belgium; J. Teghem, J.-M. Charlet. 13. Rough Sets and Some Aspects of Logic Synthesis; T. Łuba, J. Rybnik. Part II: Comparison with Related Methodologies. 1. Putting Rough Sets and Fuzzy Sets together; D. Dubois, H. Prade. 2. Applications of Fuzzy-Rough Classification to Logics; A. Nakamura. 3. Comparison of the Rough Sets Approach and Probalistic Data Analysis Techniques on a Common Set of Medical Data; E. Krusinska, A. Babic, R. Słowinski, J. Stefanowski. 4. Some Experiments to Compare Rough Sets Theory and Ordinal Statistical Methods; J. Teghem, M. Benjelloun. 5. Topological and Fuzzy Rough Sets; T. Lin. 6. On Convergence of Rough Sets; L.T. Polkowski. Part III: Further Developments. 1. Maintenance of Knowledge in Dynamic Systems; M.E. Orlowska, M.W. Orlowski. 2. The Discernibility Matrices and Functions in Information Systems; A. Skowron, C. Rauszer. 3. Sensitivity of Rough Classification to Changes in Norms of Attributes; K. Słowinski, R. Słowinksi. 4. Discretization of Condition Attributes Space; A. Lenarcik, Z. Piasta. 5. Consequence Relations and Information Systems; D. Vakarelov. 6. Rough Grammar for High Performance Management of Processes on a Distributed System; Z.M. Wójcik, B.E. Wójcik. 7. Learning Classification Rules from Database in the Context of Knowledge-Acquisition and Representation; R. Yasdi. 8. 'RoughDAS' and 'RoughClass' Software Implementations of the Rough Sets Approach; R. Słowinski, J. Stefanowski. Appendix: Glossary of Basic Concepts. Subject Index.