Hybrid Framework Parameterization Reduction Combination in Soft Set

Autor:	Wan Maseri Binti Wan Mohd, Haruna Chiroma, Mohammed Adam Taheir Mohammed, Ruzaini Abdullah Arshah, Mungad Mungad, Edi Sutoyo
Rok vydání:	2019
Předmět:	Set (abstract data type) Reduction (complexity) Computer science Process (computing) Volume (computing) Data mining computer.software_genre computer Soft set
Zdroj:	Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) ISBN: 9789811317972 DaEng
DOI:	10.1007/978-981-13-1799-6_25
Popis:	Voluminous data are available in soft sets, which makes it difficult to recognize the soft set decisions of the data. The large increase in the volume of these soft set has made it necessary to enlarge the size of the storage media to store the data. Consequently, several researches have proposed oft set reduction of the data. This paper proposes uncertain soft set by hybridizing two soft set reduction techniques producing a significant result without affecting the decisive characteristics of the data. This proposed method utilizes advanced techniques to govern knowledge with proper reduction of related resources that can assist the decision-making process.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6b03d8ac2c4ad672fc97fc19b4a7013d https://doi.org/10.1007/978-981-13-1799-6_25 Zobrazit plný text záznamu