Dotnet a rough-set-based incremental approach for updating approximations under dynamic maintenance environments
0 likes27 views
This document discusses a new incremental method for updating approximations in a variable precision rough-set model when objects in an information system are dynamically changing over time. The method utilizes previous data structures to efficiently carry out incremental updates to approximations as objects evolve. It also considers changes to an attribute's domain to update approximations incrementally under a variable precision rough-set model. An experimental evaluation demonstrates the efficiency of the proposed incremental updating method for dynamic maintenance of approximations.
1 of 1
Download to read offline
More Related Content
What's hot (9)
Ad
Viewers also liked (19)
Ad
Similar to Dotnet a rough-set-based incremental approach for updating approximations under dynamic maintenance environments (20)
Dotnet a rough-set-based incremental approach for updating approximations under dynamic maintenance environments
- 1. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com A ROUGH-SET-BASED INCREMENTAL APPROACH FOR UPDATING APPROXIMATIONS UNDER DYNAMIC MAINTENANCE ENVIRONMENTS ABSTRACT: Approximations of a concept by a variable precision rough-set model (VPRS) usually vary under a dynamic information system environment. It is thus effective to carry out incremental updating approximations by utilizing previous data structures. This paper focuses on a new incremental method for updating approximations of VPRS while objects in the information system dynamically alter. It discusses properties of information granulation and approximations under the dynamic environment while objects in the universe evolve over time. The variation of an attribute's domain is also considered to perform incremental updating for approximations under VPRS. Finally, an extensive experimental evaluation validates the efficiency of the proposed method for dynamic maintenance of VPRS approximations.