Application of curve-fitting techniques to develop numerical calibration procedures for a river water quality model

Cui, Fenghao; Park, Chul; Kim, Moonil

doi:10.1016/j.jenvman.2019.109375

Cited by 20 publications

(7 citation statements)

References 32 publications

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“…54,55 The quality of the extracted features were estimated, and a robust least square tool was used to support model application and data analysis. 56 In our study, Figure 6(c) shows the RMS of the force and vibration in the curve fitting is closely fitted to the regression line. The maximum RMS observed in Figure 6(c), because of the transfer of vibration from the handpiece 49 and maybe the cause of material dislodging.…”

Section: Discussionsupporting

confidence: 55%

Force and vibration analysis in biomechanical preparation of root canals using reciprocating endodontic file system: In vitro study

Thakur

Kankar

Parey

et al. 2021

Proc Inst Mech Eng H

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The shaping and cleaning of the root canal are very important in root canal treatment. The excessive force and vibration during biomechanical preparation of the root canal may result in failure of the endodontic file. In this study, force and vibration analysis was carried out during root canal preparation. The samples of human extracted (premolar) teeth were provided by the College of Dental Science and Hospital. Endodontic instruments for reciprocating motion, such as the WaveOne Gold file system, had been used for root canal preparation. Force and vibration signals were recorded by dynamometer and accelerometer, respectively. The acquired signals were denoised using the db4 (SWT denoising 1-D) wavelet. Four levels of decomposition were carried out for each signal. The signal denoising technique was used to remove unwanted noise from the acquired signal. FESEM analysis was used to visualize the levels of severity of endodontic files during the cleaning and shaping of the root canal. In most of the cases, the failure occurred due to the improper use of the root canal instrumentation. The optimum amount of force was used to avoid the file failure and provided the proper instrumentation. The curve fitting regression model was used to find the interdependency between force and vibration.

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Section: Discussionsupporting

confidence: 55%

Force and vibration analysis in biomechanical preparation of root canals using reciprocating endodontic file system: In vitro study

Thakur

Kankar

Parey

et al. 2021

Proc Inst Mech Eng H

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“…BOD is affected by COD in a positive direction [19] and by TKN and NH 4 -N in a negative direction. COD is explained by BOD, NH 4 -N, T and TSS by 80 % and the effect of all four variables is positive [29]. NH 4 -N is explained by the variables of BOD, COD and TKN by 40.5 %.…”

Section: The Prediction Of Relationship Among the Variables Through Mmentioning

confidence: 93%

Prediction of Water Quality in Riva River Watershed

Öz

Topal

Uzun

2019

Ecological Chemistry and Engineering S

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The Riva River is a water basin located within the borders of Istanbul in the Marmara Region (Turkey) in the south-north direction. Water samples were taken for the 35 km drainage area of the Riva River Basin before the river flows into the Black Sea at 4 stations on the Riva River every month and analyses were carried out. Changes were observed in the quality of water from upstream to downstream. For this purpose, the spatial and temporal variations of water quality were investigated using 13 water quality variables with the ANOVA test. It was observed that COD, DO, S and BOD were important in determining the spatial variation. On the other hand, it was found out that all the variables were effective in determining the temporal variation. Moreover, the correlation analysis which was carried out in order to assess the relations between water quality variables showed that the variables of BOD-COD, BOD-EC, COD-EC, BOD-T and COD-T were correlated and the regression analysis showed that COD, TKN and NH4-N explained BOD and BOD, NH4-N, T and TSS explained COD by approximately 80 %. Consequently, the Artificial Neural Network (ANN), Decision Tree and Logistic Regression models were developed using the data of training set in order to predict the water quality classes of the variables of COD, BOD and NH4-N. Quality classes were predicted for the variables by inputting the data of testing set into the developed models. According to these results, it was seen that the ANN was the best prediction model for COD, the Decision Tree for BOD and the ANN and Decision Tree for NH4-N.

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“…The least residual method, a commonly used curve fitting technique, is based on the minimum sum of residuals (Cui et al , 2019). Consider (x i , y i ) as data points on the x - and y -axes where i = 0,1, 2… N where N is the number of data points.…”

Section: Proposed Gaussian Exponential Regressionmentioning

confidence: 99%

“…The second stage of a regression study is selecting an appropriate algorithm for determining unknown coefficients in the base equation. In literature, many curve fitting techniques such as the Householder least square technique (Elzinga et al , 2000), least residual technique (Cui et al , 2019) and genetic algorithm–based curve fitting technique (Karr et al , 1991) are presented. The most commonly used method is the least residual algorithm (LRA), which involves solving differential equations.…”

Section: Introductionmentioning

confidence: 99%

Gaussian exponential regression method for modeling open circuit voltage of lithium-ion battery as a function of state of charge

Vyas

Shah

Vijay

et al. 2021

COMPEL

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Purpose The purpose of the article is to develop an equation to accurately represent OCV as a function of SoC with reduced computational burden. Dependency of open circuit voltage (OCV) on state of charge (SoC) is often represented by either a look-up table or an equation developed by regression analysis. The accuracy is increased by either a larger data set for the look-up table or using a higher order equation for the regression analysis. Both of them increase the memory requirement in the controller. In this paper, Gaussian exponential regression methodology is proposed to represent OCV and SoC relationships accurately, with reduced memory requirement. Design/methodology/approach Incremental OCV test under constant temperature provides a data set of OCV and SoC. This data set is subjected to polynomial, Gaussian and the proposed Gaussian exponential equations. The unknown coefficients of these equations are obtained by least residual algorithm and differential evolution–based fitting algorithms for charging, discharging and average OCV. Findings Root mean square error (RMSE) of the proposed equation for differential evolution–based fitting technique is 35% less than second-order Gaussian and 74% less than a fifth-order polynomial equation for average OCV with a 16.66% reduction in number of coefficients, thereby reducing memory requirement. Originality/value The knee structure in the OCV and SoC relationship is accurately represented by Gaussian first-order equation, and the exponential equation can accurately describe the linear relation. Therefore, this paper proposes a Gaussian exponential equation that accurately represents the OCV as a function of SoC. The results obtained from the proposed regression methodology are compared with the polynomial and Gaussian regression in terms of RMSE, mean average, variance and number of coefficients.

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Application of curve-fitting techniques to develop numerical calibration procedures for a river water quality model

Cited by 20 publications

References 32 publications

Force and vibration analysis in biomechanical preparation of root canals using reciprocating endodontic file system: In vitro study

Force and vibration analysis in biomechanical preparation of root canals using reciprocating endodontic file system: In vitro study

Prediction of Water Quality in Riva River Watershed

Gaussian exponential regression method for modeling open circuit voltage of lithium-ion battery as a function of state of charge

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