An Ideal Technique for Decision-Making Problems for Uncertain Data and Its Application In Medical Science
Meena Arora
Dr. Meena Arora, Department of Information Technology, JSS Academy of Technical Education,, Noida, India.
Manuscript received on 21 August 2019. | Revised Manuscript received on 10 September 2019. | Manuscript published on 30 September 2019. | PP: 923-927 | Volume-8 Issue-11, September 2019. | Retrieval Number: K15630981119/2019©BEIESP | DOI: 10.35940/ijitee.K1563.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: For representing and manipulating uncertain information like fuzzy, incomplete, inconsistent or imprecise, Neutrosophic relation database model is a more general platform, in the human decision-making process. Neutrosophic sets can easily handle real world problems. A new correlation method is introduced in this paper to construct similarity measure, by which decision making problem that exist in real world situation can be easily handled in regard of multiple existing criteria’s or incomplete or inconsistent information. The selection of the best option of alternative can be done by ranking all the other options as per similarity measure depending on concept of similarity. Later in this paper, an explanatory example is given of the proposed method and the comparison results are also presented to show the effective output.. The application in certain domains of medical diagnosis problems having multiple criteria’s in decision making are also discussed in the end of the proposed method.
Keywords: Maximum approximation, Minimum approximation, Efficient decision making, Similarity measure.
Scope of the Article: Bio-Science and Bio-Technology