• 대한기계학회논문집
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• 제17권11호
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• pp.2684-2693
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• 1993

The free vibration and dynamic response of cross-ply for CFRP and GFRP laminated circular cylindrical shells under dynamic loadings are investigated by using the first-order shear deformation shell theory. The modal analysis technique is used to develop the analytical solutions of simply supported cylindrical shells under dynamic load. The analysis is based on an expansion of the loads, displacements and rotations in a double Fourier series which satisfies the and boundary conditions of simply support. Analytical solution is assumed to be separable into a function of time and a function of position. In this paper, the considered load forces are step pulse, sine pulse, triangular(1, 2, 3) pulse and exponential pulse. The solution for a given loading pulse can be found by involving the convolution integral. The results show that the dynamic response are governed primarily by the natural period of the structure.

• 한국항행학회논문지
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• 제16권4호
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• pp.635-640
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• 2012

본 논문에서는 접지된 2개의 유전체층 위의 도체띠 격자구조에 의한 TE (Transverse Electric) 산란문제를 도체경계조건과 수치해석 방법인 FGMM (Fourier-Galerkin Moment Method)를 적용하여 해석하였으며, 이 때 유도되는 표면전류밀도는 미지의 계수와 단순한 함수인 지수함수의 곱의 급수로 전개하였다. 전반적으로, 제안된 구조에서 영역-2의 유전체층의 비유전율 ${\epsilon}_{r2}$과 유전체 층의 두께 $t_2$가 증가함에 따라 반사전력이 증가하였다. 반사전력의 급변점들은 공진효과에 기인한 것으로 과거에 wood's anomaly라고 불리워졌으며, 수치계산 결과들은 기존 논문의 결과들과 일치하였다.

• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.244-253
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• 2013

In industries, shipping is an important issue in improving the forecasting accuracy of sales. This paper introduces a hybrid method and plural methods are compared. Focusing the equation of exponential smoothing method (ESM) that is equivalent to (1, 1) order autoregressive-moving-average (ARMA) model equation, a new method of estimating the smoothing constant in ESM had been proposed previously by us which satisfies minimum variance of forecasting error. Generally, the smoothing constant is selected arbitrarily. However, this paper utilizes the above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate the smoothing constant. Thus, theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This method is executed in the following method. Trend removing by the combination of linear and 2nd order nonlinear function and 3rd order nonlinear function is executed to the original production data of two kinds of bread. Genetic algorithm is utilized to search the optimal weight for the weighting parameters of linear and nonlinear function. For comparison, the monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.

• 대한원격탐사학회지
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• 제28권6호
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• pp.597-609
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• 2012

Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of IKONOS, Landsat TM, and MODIS satellite images using empirical models and demonstrates its use with data collected at Missouri field sites. LAI data were obtained several times during the 2002 growing season at monitoring sites established in two central Missouri experimental fields, one planted to soybean (Glycine max L.) and the other planted to corn (Zea mays L.). Satellite images at varying spatial and spectral resolutions were acquired and the data were extracted to calculate normalized difference vegetation index (NDVI) after geometric and atmospheric correction. Linear, exponential, and expolinear models were developed to relate temporal NDVI to measured LAI data. Models using IKONOS NDVI estimated LAI of both soybean and corn better than those using Landsat TM or MODIS NDVI. Expolinear models provided more accurate results than linear or exponential models.

• 한국토양비료학회지
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• 제46권4호
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• pp.245-252
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• 2013

Leaf area index (LAI) is important in explaining the ability of crops to intercept solar energy for biomass production, amount of plant transpiration, and in understanding the impact of crop management practices on crop growth. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of RapidEye imagery obtained from 2010 to 2012 using empirical models in a rice plain in Seosan, Chungcheongnam-do. Rice plants were sampled every two weeks to investigate LAI, fresh and dry biomass from late May to early October. RapidEye images were taken from June to September every year and corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). Linear, exponential, and expolinear models were developed to relate temporal satellite NDVIs to measured LAI. The expolinear model provided more accurate results to predict LAI than linear or exponential models based on root mean square error. The LAI distribution was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when RapidEye imagery was applied to expolinear model. The spatial trend of LAI corresponded with the variation in the vegetation growth condition.

• 충청수학회지
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• 제24권2호
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• pp.187-204
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• 2011

B. C. Carlson [Some extensions of Lardner's relations between $_0F_3$ and Bessel functions, SIAM J. Math. Anal. 1(2) (1970), 232-242] presented several useful relations between Bessel and generalized hypergeometric functions that generalize some earlier results. Here, by simply splitting Srivastava's hypergeometric function $H_B$ into eight parts, we show how some useful and generalized relations between Srivastava's hypergeometric functions $H_B$ and $F^{(3)}$ can be obtained. These main results are shown to be specialized to yield certain relations between functions $_0F_1$, $_1F_1$, $_0F_3$, ${\Psi}_2$, and their products including different combinations with different values of parameters and signs of variables. We also consider some other interesting relations between the Humbert ${\Psi}_2$ function and $Kamp\acute{e}$ de $F\acute{e}riet$ function, and between the product of exponential and Bessel functions with $Kamp\acute{e}$ de $F\acute{e}riet$ functions.

• 산업경영시스템학회지
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• 제39권1호
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• 대한기계학회논문집A
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• 제34권4호
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• pp.457-465
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• 2010

본 연구에서는 McVetty 와 Monkman-Grant 의 모델에 기초하여 만들어진 새로운 크리프 수명예측 모델인 Taylor 급수(T-S) 모델을 제안하였다. 본 모델은 회귀분석에서 발생하는 오차를 줄이기 위하여 McVetty 모델에서 sinh 함수를 Taylor 급수에 의해 변환한 후 첫 3 개항을 취한 것으로서 모델중의 상수 값은 통계학적 방법인 최대가능성 기법을 이용하여 결정되었다. T-S 모델을 이용하여 Alloy 617 의 크리프 수명을 예측한 결과 Eno, 지수함수 및 Larson-Miller(L-M) 방법에 비해 더 정확한 예측을 하는 것으로 나타났다. 또한 T-S 모델은 특정 온도에서 크리프 수명 예측을 할 수 있는 등온 T-S(IT-S) 모델로 표현될 수 있었으며, IT-S 모델은 Alloy 617 의 장시간 크리프 수명예측에서 가장 좋은 예측을 하는 것으로 나타났다.

• 인터넷정보학회논문지
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• 제25권2호
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• pp.93-99
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• 2024

본 논문에서는 점프 항을 포함하는 이자율 기간구조 모형의 채권 가격을 결정하기 위하여 이토의 보조정리(Ito's Lemma)를 적용하여 채권가격편미분방정식(Partial Differential Bond Price Equation; PDBPE)을 유도한다. PDBPE으로부터, 지수함수에 대한 매클로린 급수 (Maclaurin series; MS)와 적률생성함수(moment-generating function; MGF)를 이용하여 채권 가격의 수치해(Numerical Solution; NS)를 구한다. 그리고 몬테 카르로 시뮬레이션(Monte Carlo Simulation; MCS) 기법을 이용하여 채권의 가격을 결정하기 위한 알고리즘을 제안하고, 시뮬레이션 과정을 통하여 채권의 가격을 결정한다. 수치적 분석을 이용한 채권 가격의 NS와 MCS를 이용하여 얻은 채권 가격의 결과를 비교하기 위하여, NS의 값과 MCS의 값의 비율인 상대오차(Relative Error; RE)를 구한다. 이로부터 얻은 RE가 약 2.2%보다 작음을 확인할 수 있고, 이것은 수치적 분석뿐만 아니라 제안한 알고리즘을 이용해도 채권의 가격을 매우 정확하게 예측할 수 있음을 의미한다. 또한, 지수함수에 대한 MS를 이용하여 얻은 채권 가격의 NS가 MGF를 적용하여 구한 채권 가격의 NS보다 상대적으로 오차가 작다는 것을 확인할 수 있다.

• 전력전자학회논문지
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• 제7권3호
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• pp.244-252
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• 2002

본 논문에서는 가변속 교류 전동기 구동에 많이 사용되는 3상 ac/dc/ac PWM 컨버터 시스템에서의 직류링크 리플전류를 주파수 영역에서 해석하고자 한다. 고조파 전류는 컨버터의 스위칭함수와 지수함수 형태의 퓨리에 급수 전개를 이용하여 분석된다. 전원측 컨버터와 부하측 인버터의 스위칭 주기간의 변위각과 비동기 PW이 리플전류에 미치는 영향도 고찰된다. 해석 결과가 PSIM을 이용한 시뮬레이션으로부터 나온 고조파 스펙트럼과 잘 일치함을 확인한다 제시된 해석기법은 PWM의 원리에 대한 이해를 돕고, 해석 결과는 직류링크 커패시터의 고주파 등가 모델링에 이용된다.