In this chapter, the basics of the rough set approach are presented, and an outline of an exemplary processor structure is given. The organization of a simple processor is based on elementary rough set granules and dependencies between them. The rough set processor (RSP) is meant to be used as an additional fast classification unit in ordinary computers or as an autonomous learning machine. In ...

Abs t rac t . Knowledge discovery in databases, or data mining, is an important objective in the development of dataand knowledge-base systems. An attributeoriented rough set method is developed for knowledge discovery in databases. The method integrates learning from example techniques with rough set theory. An attribute-oriented concept tree ascension technique is first applied in generalizat...

Fuzzy covering-based rough set models are hybrid models using both rough set and fuzzy set theory. The former is often used to deal with uncertain and incomplete information, while the latter is used to describe vague concepts. The study of fuzzy rough set models has provided very good tools for machine learning algorithms such as feature and instance selection. In this article, we discuss diff...

Bipolar neutrosophic set theory and rough neutrosophic set theory are emerging as powerful tool for dealing with uncertainty, and indeterminate, incomlete, and inprecise information. In the present study we develop a hybrid structure called “rough bipoar neutrsophic set”. In the study, we define rough bipoar neutrsophic set and define union, complement, intersection and containment of rough bip...

The principle of the minority subordinate to the majority is the most feasible and credible when people make decisions in real world. So generalized multigranulation rough set theory is a desirable fusion method, in which upper and lower approximations are approximated by granular structures satisfying a certain level of information. However, the relationship between a equivalence class and a c...

This article introduces a general framework of multi-granulation fuzzy probabilistic roughsets (MG-FPRSs) models in multi-granulation fuzzy probabilistic approximation space over twouniverses. Four types of MG-FPRSs are established, by the four different conditional probabilitiesof fuzzy event. For different constraints on parameters, we obtain four kinds of each type MG-FPRSs...

As an alternative to the price-based traditional auction model, the multi-attribute auction model is an integrated model requiring the simultaneous trade of different types of attributes as the sellers and buyers deal. As a result, the design and modeling of the auction mechanism have become very difficult. This paper proposes a multiattribute auction model using the dominance-based rough sets ...

Credit scoring analysis is an important activity, especially nowadays after a huge number of defaults has been one of the main causes of the financial crisis. Among the many different tools used to model credit risk, the recent development of rough set models has proved effective. The original development of rough set theory has been widely generalized and combined with other approaches to unce...

This study differs from previous ones applying multivariate statistical analysis and multiple criteria decision-making (MCDM) methods. We use the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) to formulate airline service strategies by generating airline service decision rules thatmodelpassengerpreferences for airline servicequality. Flowgraphsare applied to inferdecision rul...