Research On Some Problems In Distributed Full Fuzzy Decision Information Systems

An information system is an important model in the field of artificial intelligence.As the basic structure of an information system,information structure is an important research content of information system.Measurement uncertainty as an evaluation tool,is an important research topic in machine learning.In this dissertation,we mainly study some problems in distributed full fuzzy decision information systems.Chapter 2 has systematically studied the fuzzy information structure and measurement uncertainty of full fuzzy information systems.Theoretical studies,numerical experiments and effectiveness analysis show that granulation measure and entropy measure can be used to measure uncertainty for full fuzzy information systems.These results will be helpful for rule evaluation in a full fuzzy information system and understanding the essence of its uncertainty.Chapter 3 has studied the fuzzy information structure and measurement uncertainty of distributed full fuzzy information systems.These measurements can be applied to feature selection and data mining,and may have potential applications in knowledge discovery of distributed full fuzzy information systems.Chapter 4 has studied a multi-granulation decision-theoretic rough set method for distributed f c-decision information systems and attempt applying this method to medical diagnosis.These results will be helpful for dealing with distributed fuzzy data and significant for establishing a framework of multi-granulation decision rough sets in distributed f c-decision information systems.