Letter: The concept of stratification and future applications

Rajabi Asadabadi, M; Saberi, M; Chang, E

Letter: The concept of stratification and future applications

Rajabi Asadabadi, M Saberi, M

Chang, E

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Publication Type:: Journal Article
Citation:: Applied Soft Computing Journal, 2018, 66 pp. 292 - 296
Issue Date:: 2018-05-01

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Field	Value	Language
dc.contributor.author	Rajabi Asadabadi, M	en_US
dc.contributor.author	Saberi, M https://orcid.org/0000-0002-5168-2078	en_US
dc.contributor.author	Chang, E	en_US
dc.date.available	2020-05-25T19:15:22Z
dc.date.issued	2018-05-01	en_US
dc.identifier.citation	Applied Soft Computing Journal, 2018, 66 pp. 292 - 296	en_US
dc.identifier.issn	1568-4946	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133060
dc.description.abstract	© 2018 Elsevier B.V. The main purpose of this letter is to draw attention to a recent concept, namely Concept of Stratification (CST) developed by Zadeh [1]. CST describes a system that transitions through a number of states in order to arrive at a desired state. CST is a problem-solving approach, which is easy while effective. Therefore, CST seems very likely to emerge in coming years as a major interest area in areas such as soft computing, Artificial Intelligence (AI), robotics, Natural Language Processing (NLP), and big data. In this expository letter, the advantages and the main shortcoming of CST are reviewed. The concept is explained and areas that the concept is likely to be applied are discussed. Considering the generality of the original CST proposed by Zadeh, it is possible to consider different versions for CST to be applied in future studies. Hence, versions of CST including fuzzy CST, a 3DCST, and multiple systems and multiple CSTs are presented. This work is a first step in a vast range of applications of CST. Researchers, especially those applying soft computing tools such as fuzzy sets theory and granulation, are encouraged to examine the capability of CST in addressing significant real-world problems.	en_US
dc.relation.ispartof	Applied Soft Computing Journal	en_US
dc.relation.isbasedon	10.1016/j.asoc.2018.02.035	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Letter: The concept of stratification and future applications	en_US
dc.type	Journal Article
utslib.citation.volume	66	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0102 Applied Mathematics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	66	en_US

Abstract:

© 2018 Elsevier B.V. The main purpose of this letter is to draw attention to a recent concept, namely Concept of Stratification (CST) developed by Zadeh [1]. CST describes a system that transitions through a number of states in order to arrive at a desired state. CST is a problem-solving approach, which is easy while effective. Therefore, CST seems very likely to emerge in coming years as a major interest area in areas such as soft computing, Artificial Intelligence (AI), robotics, Natural Language Processing (NLP), and big data. In this expository letter, the advantages and the main shortcoming of CST are reviewed. The concept is explained and areas that the concept is likely to be applied are discussed. Considering the generality of the original CST proposed by Zadeh, it is possible to consider different versions for CST to be applied in future studies. Hence, versions of CST including fuzzy CST, a 3DCST, and multiple systems and multiple CSTs are presented. This work is a first step in a vast range of applications of CST. Researchers, especially those applying soft computing tools such as fuzzy sets theory and granulation, are encouraged to examine the capability of CST in addressing significant real-world problems.

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http://hdl.handle.net/10453/133060