Hybrid Filter for Object Reduction

Mohammed, Mohammed Adam Taheir and Wan Maseri, Wan Mohd and Ruzaini, Abdullah Arshah (2014) Hybrid Filter for Object Reduction. International Journal of Basic and Applied Sciences, 3 (1). pp. 55-58. ISSN 2227-5053. (Published)

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The basic idea to build significant attribute the uncertain objects should remove. Several theories are dealing with uncertainty, soft set theory also handles this uncertainty problem which still an open area to be explored in knowledge management. The propose techniques Known as Filtering data set which used for maintained the inferior object and we need to look at the other side of attribute reduction. The propose technique are reducing the size of object firstly, then the Hybrid reduction are executed for generating the decision extractions. These filters have reduced the size of memory without losing the characteristic of information which absolutely highly efficient. By using Filtering the inferior object of Hybrid techniques are managed. As part of this proposal, an analysis of Hybrid reduction techniques. In the conclusion part Filtering the Hybrid show better result compared to Hybrid reduction.

Item Type: Article
Uncontrolled Keywords: Object Reduction; Object Extractions; Parameters Reductions
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 28 Oct 2015 01:57
Last Modified: 18 May 2018 02:26
URI: http://umpir.ump.edu.my/id/eprint/5992
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