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Neutrosophic Non-linear Regression based on Kuhn-Tucker Necessary Conditions |
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PP: 49-59 |
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doi:10.18576/jsap/120105
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Author(s) |
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Mahmoud A. Abo-Sinna,
Nagwa G. Ragab,
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Abstract |
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| Correlation coefficient and regression analysis are the most applied statistical approaches accessible in numerous disciplines due to its applicability and relevance. The neutrosophic sets found their place into recent research, whereas the world is full of indeterminacy. Kuhn-Tuckers necessary conditions are used to obtain the estimated parameters for non-linear regression models. This estimation procedure can use for any data set of non-linear regression models. We present, in this paper, the concepts of neutrosophic correlation and non-linear regression based on Kuhn-Tuckers necessary conditions. we provide some comparative studies between single-valued neutrosophic set and interval-valued neutrosophic set. Next, we apply scoring methods by different research. Numerical example is given to explain the result presented in this study. The results showed that the proposed approach can yield a fitting curve for any data set in neutrosophic environment.
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