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Rule Detection in Mobile Ad Hoc Network using Rough Set and Probability

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Authors:
P. Seethalakshmi, S. Senthilkumar
10.5120/ijca2021920987

P Seethalakshmi and S Senthilkumar. Rule Detection in Mobile Ad Hoc Network using Rough Set and Probability. International Journal of Computer Applications 174(11):20-24, January 2021. BibTeX

@article{10.5120/ijca2021920987,
	author = {P. Seethalakshmi and S. Senthilkumar},
	title = {Rule Detection in Mobile Ad Hoc Network using Rough Set and Probability},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2021},
	volume = {174},
	number = {11},
	month = {Jan},
	year = {2021},
	issn = {0975-8887},
	pages = {20-24},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume174/number11/31721-2021920987},
	doi = {10.5120/ijca2021920987},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This paper proposes an innovative approach for rule detection from a decision table. The aim is to apply rough set concepts and probabilistic properties to search for rule discovery. Rough set theory is generally a comparatively new intelligent technique used within the invention of data of knowledge dependencies; it evaluates the importance of attributes, discovers the patterns of information, reduces all redundant objects and attributes, and seeks the minimum subset of attributes. Moreover, it is getting used for the extraction of rules from databases. With every decision rule in decision table, two conditional probabilities, the certainty and the coverage coefficient of the rule are associated. The Probabilistic approach is an extension of the Rough set approach that reveals some probabilistic structure of the data being analyzed. Finally, these techniques will be applied for finding rules in mobile ad hoc network for the selection of best routing path with minimum number of resources.

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Keywords

Rough Set; Entropy; Information gain; Certainty and Coverage; Decision rule.