Rough Sets and Knowledge Technology: 8th International - download pdf or read online

By Marcin Szczuka (auth.), Pawan Lingras, Marcin Wolski, Chris Cornelis, Sushmita Mitra, Piotr Wasilewski (eds.)

ISBN-10: 364241298X

ISBN-13: 9783642412981

ISBN-10: 3642412998

ISBN-13: 9783642412998

This ebook constitutes the completely refereed convention lawsuits of the eighth foreign convention on tough units and data know-how, RSKT 2013, held in Halifax, Canada in October 2013 as one of many co-located meetings of the 2013 Joint tough Set Symposium, JRS 2013. The sixty nine papers (including forty four common and 25 brief papers) integrated within the JRS court cases (LNCS 8170 and LNCS 8171) have been conscientiously reviewed and chosen from 106 submissions. The papers during this quantity hide issues resembling historical past and way forward for tough units; foundations and probabilistic tough units; ideas, reducts, ensembles; new tendencies in computing; three-way choice tough units; and studying, predicting, modeling.

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Extra resources for Rough Sets and Knowledge Technology: 8th International Conference, RSKT 2013, Halifax, NS, Canada, October 11-14, 2013, Proceedings

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The other is a demonstration of a basic principle of granular computing and, hence, makes it easily understandable and applicable to a wide range of applications. 2 An Overview of Three-Way Decisions By extending the three-way classification of rough set theory and synthesizing results across many disciplines, I examined a theory of three-way decisions in an earlier paper [29]. The main results are briefly reviewed in this section. Suppose U is a finite nonempty set of objects and C is a finite set of conditions.

Sequential three-way decisions are particularly useful for practical decision-making problems when information is unavailable and is acquired on demands with associated cost. Sequential three-way decisions are much more complicated than simple twoway decisions. There are many challenging issues. One must construct multiple levels of granularity and multiple representations of the same object. One must consider more parameters, such as the number of levels, evaluations at different levels, and the thresholds at each level.

The relation denotes a “finer than” relationship between different descriptions. A description at a coarser level is more abstract by removing some details of description in a finer level. It may be commented that the languages used to describe objects may be different at different levels. Consequently, the processing methods and costs may also be different. Multiple Evaluations of Objects. Due to different representations at different levels, we need to consider different evaluations too. Let vi , 0 ≤ i ≤ n, denote an evaluation at level i whose values are from a totally ordered sets (Li , i ).

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Rough Sets and Knowledge Technology: 8th International Conference, RSKT 2013, Halifax, NS, Canada, October 11-14, 2013, Proceedings by Marcin Szczuka (auth.), Pawan Lingras, Marcin Wolski, Chris Cornelis, Sushmita Mitra, Piotr Wasilewski (eds.)


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