Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 193, Issue 3, Pages 891-903Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2007.10.053
Keywords
Transportation; Data mining; Rough sets
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The paper presents a process of technical diagnostic applied to a fleet of vehicles utilized in the delivery system of express mail. It is focused on evaluation of diagnostic capacity of particular characteristics, reduction of a set of initially selected characteristics to a minimal and satisfactory subset, recognition of a technical condition of vehicles resulting in their condition-based classification. In addition, the decision rules facilitating technical diagnostic and management of a fleet of vehicles are generated and utilized. N-fold cross validation is applied to estimate the efficiency of the decision rules. The rough set theory is applied to support the diagnostic process of vehicles. Classical rough set (CRS) theory is compared with the dominance-based rough set (DRS) approach. The results of computational experiments for both approaches are compared. (C) 2007 Elsevier B.V. All rights reserved.
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