• Journal of the Chungcheong Mathematical Society
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• v.30 no.4
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• pp.397-409
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• 2017

In this paper, we investigated the extinction, positivity, and decay estimates of the solutions to the initial-boundary value problem of the semilinear parabolic equation with nonlinear gradient source and interior absorption terms by using the integral norm estimate method. We found that the decay estimates depend on the choices of initial data, coefficients and domain, and the first eigenvalue of the Laplacean operator with homogeneous Dirichlet boundary condition plays an important role in the proofs of main results.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.185-196
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• 1999

This paper is concerned with investigating the global asymptotic behavior of the solution to a nonlinear wave equation with variable coefficients. noreover an estimate of the rate of decay of the solution is obtained.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• The Journal of Natural Sciences
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• v.8 no.1
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• pp.5-15
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• 1995

The equation error formulation in the adaptive IIR filtering provides convergence to a global minimum regardless a local minimum with a large stability margin. However, the equation error formulation suffers from the bias in the coefficient estimates. In this paper, a new algorithm, which does not require a prespecification of the noise variance, is proposed for the equation error formulation. This algorithm is based on the equation error smoothing and provides an unbiased parameter estimate in the presence of white noise. Through simulations, it is demonstrated that the algorithm eliminates the bias in the parameter estimate while retaining good properties of the equation error formulation such as fast convergence speed and the large stability margin.

• KCID journal
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• v.14 no.1
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• pp.41-49
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• 2007

In this study, Kajiyama equation and SWAT model were used to estimate the available water resources from 1967 to 2003 at the small scale watershed, located in Dongnae-Myeon, Chunchen, Gangwon. The annual average streamflow for dry years estimated using the Kajiyama equation and the SWAT model were $2,593,779m^3$ and $2,579,162m^3$. The annual average streamflow for wet years were $7,223,804m^3$ and $7,035,253m^3$, respectively. The annual arrange streamflow for the entire 36 year period were $14,868,601m^3$ and $14,214,292m^3$, respectively. The coefficient of determination ($R^2$) and the Nash-Sutcliffe coefficient for comparison between Kajiyama and SWAT were 0.90 and 0.79, respectively. The comparison indicates that the Kajiyama equation and the SWAT model can be used to estimate the streamflow at th study watershed with reasonable accuracy, although the estimated values were not compared with measured streamflow data, which is not available at the small scale study watershed. However, the Kajiyama equation is recommended for estimating available water resources at Dongnae-Myeon watershed because of its ease-of-use and reasonable accuracy compared with the SWAT model, requiring numerous model input and expensive GIS software in operating the model

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.55-66
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• 1992

The energy and momentum coefficients ${\alpha}$ and ${\beta}$ are measures of homogenerity of velocity distribution in a chanel section. They indicate the effect of energy and momentum transport. However, in most practical applications, they are assumed to be unity due to the difficulty in estimating them. Efforts have been made in this study to estimate these coefficients and to develop equations for practical applications. The Prandtl-von Karman logarithmic equation as being used today has limitations and far-reaching assumptions. Therefore, this paper uses Chiu's velocity distribution equation which seems to be capable of serving as such an alternative, to estimate the velocity distribution and the energy and momentum coefficients, ${\alpha}$ and ${\beta}$ results are compared with those computed by other existing equations. For practical applications, this paper also uses Chiu's equation along with the Mannig's equation to calculate ${\alpha}$, ${\beta}$ without velocity data

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.4
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• pp.303-310
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• 2020

Estimating the accurate internal state of lithium ion batteries to increase their safety and efficiency is crucial. Various algorithms are used to estimate the internal state of a lithium ion battery, such as the extended Kalman filter and sliding mode observer. A state-space model is essential in using algorithms to estimate the internal state of a battery. Two principal methods are used to express the state-space model, namely, continuous time and discrete time. In this work, the extended Kalman filter is employed to estimate the internal state of a battery. Moreover, this work presents and analyzes the estimation performance of algorithms consisting of a continuous time state-space model and a discrete time state-space model through static and dynamic profiles.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• Journal of Biosystems Engineering
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• v.9 no.2
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• pp.27-36
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• 1984

This study was carried out to investigate the effects of the tilling depth, tilling travel speed and soil shear stress on the tilling load characteristics and power requirement for rotary tillers. The results obtained from the study are summarized as follows. 1. The average and maximum PTO torque increased as the tilling depth, tilling pitch and soil shear stress increased. A multiple linear regression equation to estimate the average PTO torque in terms of the above parameters was developed. 2. The ratios of maximum PTO torque to the average torque were in the range of 1.17 to 1.65 for the various tilling conditions tested. The variation in PTO torque increased greatly as the tilling pitch and soil shear stress increased, but decreased as the tilling depth increased. 3. Power requirement for the PTO shaft increased with the tilling depth, travel speed and soil shear stress, but decreased slightly as the tilling pitch increased. A multiple linear regression equation to estimate power requirement for the PTO shaft in terms of the above parameters was developed. 4. The specific power requirement for the rotary tiller was in the range of $0.008-0.015ps/cm^2$ for the various tilling conditons tested. The specific tilling capacity decreased as the tilling depth and soil shear stress increased, but increased with the tilling pitch. A multiple linear regression equation to estimate the specific tilling capacity in terms of the above parameters was developed.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.163-174
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• 1999

The purpose of this paper is to obtain the solution of Fredholm-Volterra integral equation with singular kernel in the space $L_2(-1, 1)\times C(0,T), 0 \leq t \leq T< \infty$, under certain conditions,. The numerical method is used to solve the Fredholm integral equation of the second kind with weak singular kernel using the Toeplitz matrices. Also the error estimate is computed and some numerical examples are computed using the MathCad package.