Intelligent Decision Support Book

	Preface
	Scope and goals of the book
Pt. I	Applications of the rough sets approach to intelligent decision support
Ch. 1	LERS-a system for learning from examples based on rough sets	3
Ch. 2	Rough sets in computer implementation of rule-based control of industrial processes	19
Ch. 3	Analysis of diagnostic symptoms in vibroacoustic diagnostics by means of the rough sets theory	33
Ch. 4	Knowledge-based process control using rough sets	49
Ch. 5	Acquisition of control algorithms from operation data	61
Ch. 6	Rough classification of HSV patients	77
Ch. 7	Surgical wound infection - conducive factors and their mutual dependencies	95
Ch. 8	Fuzzy inference system based on rough sets and its application to medical diagnosis	111
Ch. 9	Analysis of structure - activity relationships of quaternary ammonium compounds	119
Ch. 10	Rough sets-based study of voter preference in 1988 U.S.A. presidential election	137
Ch. 11	An application of rough set theory in the control of water conditions on a polder	153
Ch. 12	Use of "rough sets" method to draw premonitory factors for earthquakes by emphasing gas geochemistry: the case of a low seismic activity context, in Belgium	165
Ch. 13	Rough sets and some aspects of logic synthesis	181
Pt. II	Comparison with related methodologies
Ch. 1	Putting rough sets and fuzzy sets together	203
Ch. 2	Applications of fuzzy-rough classifications to logics	233
Ch. 3	Comparison of the rough sets approach and probabilistic data analysis techniques on a common set of medical data	251
Ch. 4	Some experiments to compare rough sets theory and ordinal statistical methods	267
Ch. 5	Topological and fuzzy rough sets	287
Ch. 6	On convergence of rough sets	305
Pt. III	Further developments
Ch. 1	Maintenance of knowledge in dynamic information systems	315
Ch. 2	The discernibility matrices and functions in information systems	331
Ch. 3	Sensitivity of rough classification to changes in norms of attributes	363
Ch. 4	Discretization of condition attributes space	373
Ch. 5	Consequence relations and information systems	391
Ch. 6	Rough grammar for high performance management of processes on a distributed system	401
Ch. 7	Learning classification rules from database in the context of knowledge-acquisition and -representation	419
Ch. 8	'RoughDAS' and 'RoughClass' software implementations of the rough sets approach	445
	Appendix: Glossary of basic concepts	457
	Subject Index	461