Diabetes Diagnostic Model Based on Truth-value Restrictions Method Using Inference of Intuitionistic Conditional and Qualified Fuzzy Propositions
Nitesh Dhiman1, M. K. Sharma2
1M. K. Sharma, Associate Professor, Department of Mathematics, Chaudhary Charan Singh University, Meerut, India.
2Nitesh Dhiman, Research Scholar, Department of Mathematics, Chaudhary Charan Singh University, Meerut, India.
Manuscript received on December 01, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 5015-5021 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B2923129219/2019©BEIESP | DOI: 10.35940/ijeat.B2923.129219
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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: Diabetes is a challenging problem nowadays. Not only in India, but it also spreads over worldwide, In the present research paper a novel scheme based on intuitionistic fuzzy propositions to explore the knowledge base rule system with uncertainty has been developed and for the extension of fuzzy propositions to the domain of factors causing diabetes. In this paper, we have constructed the conditional and qualified intuitionistic fuzzy proposition mathematically for the diabetes diagnostic model. We have also developed an algorithm for Truth-value restriction method using the conditional and qualified intuitionistic fuzzy proposition; with the help of developed algorithm for truth-value restriction method we will give a scheme to check this severity of the diabetes. Numerical computations have also been carried out to demonstrate our approach.
Keywords: Diabetes, Intuitionistic fuzzy set, Intuitionistic fuzzy relation, Intuitionistic fuzzy propositions, PIDD, Truth-value restrictions method.