| Assessment is a process of making judgment in which information is synthesized to determine rankings. Assessment is a routine task in business management, education administration, and research and development administration. In the assessment decision system, uncertainty becomes very obvious due to the rapidly increase of the information and data. The theory of rough sets is proposed by Pawlak in practice of classification and data analysis with uncertain and incomplete information. The rough set concept can be of some importance, primarily in some branches of artificial intelligence, such as reasoning, automatic classification, pattern recognition, learning algorithms, etc. In recent years, with the development of rough set theory, the idea of rough set leads to further research and applications in classification theory, cluster analysis, measurement theory, decision-supporting, etc. The key of the rough set theory deals with the approximation of an arbitrary subset of a universe by two subsets called lower and upper approximations. Many researchers pay attention to the study of the algorithm using rough set approach, such as generation of decision rule algorithm, reduction of attributes algorithm, the parallelism algorithm and the algorithm associated the neural networks or GA with rough set and so on. The attributes reduction and decision rule generation are the kernel contents of rough set theory. Inclusion degree theory presents a unified account of various quantitative methods for uncertainty reasoning. Inclusion degree is quantitative description of containment relation. It holds the uncertainty of the relation. The inclusion degree theory and the fuzzy set theory are the important tools in studying the uncertain knowledge.Due to the uncertainty of information in the real world, the condition attributes and objective attributes could be fuzzy, therefore, this paper processes the assessment ranking in the fuzzy information system combining the concept of rough set and... |
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