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

TLDR: The 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.T. Polkowski is used.

Abstract: 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. Mrozek. 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. Luba,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. Slowinski, 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. Slowinski, R. Slowinksi. 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. Wojcik, B.E. Wojcik. 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. Slowinski, J. Stefanowski. Appendix: Glossary of Basic Concepts. Subject Index.