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http://dx.doi.org/10.22156/CS4SMB.2019.9.6.001

A Study of the Nonlinear Characteristics Improvement for a Electronic Scale using Multiple Regression Analysis  

Chae, Gyoo-Soo (Division of ICT, Baekseok University)
Publication Information
Journal of Convergence for Information Technology / v.9, no.6, 2019 , pp. 1-6 More about this Journal
Abstract
In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.
Keywords
Regression analysis; Polynomial; Non-linear; Weight estimation; Electronic scale;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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