In this study, pressure drop was measured in the pulse jet bag filter without venturi on which 16 numbers of filter bags (Ø140 × 850 ℓ) are installed according to operation condition(filtration velocity, inlet dust concentration, pulse pressure, and pulse interval) using coke dust from steel mill. The obtained 180 pressure drop test data were used to predict pressure drop with multiple regression model so that pressure drop data can be used for effective operation condition and as basic data for economical design. The prediction results showed that when filtration velocity was increased by 1%, pressure drop was increased by 2.2% which indicated that filtration velocity among operation condition was attributed on the pressure drop the most. Pressure was dropped by 1.53% when pulse pressure was increased by 1% which also confirmed that pulse pressure was the major factor affecting on the pressure drop next to filtration velocity. Meanwhile, pressure drops were found increased by 0.3% and 0.37%, respectively when inlet dust concentration and pulse interval were increased by 1% implying that the effects of inlet dust concentration and pulse interval were less as compared with those changes of filtration velocity and pulse pressure. Therefore, the larger effect on the pressure drop the pulse jet bag filter was found in the order of filtration velocity(Vf), pulse pressure(Pp), inlet dust concentration(Ci), pulse interval(Pi). Also, the prediction result of filtration velocity, inlet dust concentration, pulse pressure, and pulse interval which showed the largest effect on the pressure drop indicated that stable operation can be executed with filtration velocity less than 1.5 m/min and inlet dust concentration less than 4 g/m3. However, it was regarded that pulse pressure and pulse interval need to be adjusted when inlet dust concentration is higher than 4 g/m3. When filtration velocity and pulse pressure were examined, operation was possible regardless of changes in pulse pressure if filtration velocity was at 1.5 m/min. If filtration velocity was increased to 2 m/min. operation would be possible only when pulse pressure was set at higher than 5.8 kgf/cm2. Also, the prediction result of pressure drop with filtration velocity and pulse interval showed that operation with pulse interval less than 50 sec. should be carried out under filtration velocity at 1.5 m/min. While, pulse interval should be set at lower than 11 sec. if filtration velocity was set at 2 m/min. Under the conditions of filtration velocity lower than 1 m/min and high pulse pressure higher than 7 kgf/cm2, though pressure drop would be less, in this case, economic feasibility would be low due to increased in installation and operation cost since scale of dust collection equipment becomes larger and life of filtration bag becomes shortened due to high pulse pressure.

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

본 연구에서는 댐 용수공급능력에 영향을 미치는 요인들을 요인분석 통계기법을 사용하여 추출하였으며, 그 결과를 이용하여 댐 용수공급능력 추정을 위한 다중회귀모형을 개발하였다. 21개 다목적댐과 12개 생공용수전용댐을 대상으로 하였으며, 다목적댐과 생공용수전용댐으로 구분하여 요인분석을 수행하였다. 댐 용수공급능력에 영향을 미치는 변수로 유역면적, 유입량, 유효저수량, 생공용수량 등급, 농업용수량 등급, 하천유지유량 등급, 하천관리 등급, 평균강우량 등급을 선정하였다. 변수들의 상관계수 행렬 점검, Bartlett의 구형성 점검, KMO 표본적합도 점검을 실시하여 변수들의 요인분석에 대한 적합성을 확인하였다. 변수들은 다목적댐의 경우 3개 요인, 생공용수전용댐의 경우 2개 요인으로 분류되었으며, 요인들을 Varimax법을 사용하여 회전시켰다. 요인분석 결과는 댐 용수공급능력에 영향을 미치는 변수들이 합리적으로 선정되었고, 이들이 요인으로 적절하게 분류되었음을 보여주었다. 요인점수를 설명변수로 사용하여 연간용수공급량을 추정할 수 있는 다중회귀모형을 개발하였으며, 개발된 모형의 정확성을 평가하고 적용방법을 제시하였다. 결론적으로 댐 용수공급능력에 영향을 미치는 것으로 파악된 변수 및 요인은 댐 계획 및 설계에 유용하게 활용될 수 있을 것으로 사료된다.

The purpose of this study is to compare the relative growth of annual ring width of red pine(Pinus densiflora), black pine(Pinus thunbergii) and pitch pine(Pinus rigida) by means of multiple regression method according to Graybill hypothesis. The obtained results are as follows. 1. The changes of rainfall have affected to tree growth during the periods of 1975 through 1978. 2. Among these pine trees, red pine was mostly influenced by environmental factors. 3. The growth of annual ring width was sensitively responded to the changes of rainfall and air temperature. 4. Among the heavy metals analyzed, the concentrations(ppm) of Lead(Pb) and Copper(Cu) were negatively effected on the growth of annual ring width of pine trees. 5. The analytical technique of annual ring width may be useful for estimation of the pollution in forest areas near industrial complexes.

본 연구에서는 다중회귀분석을 이용하여 산악효과를 야기하는 지형인자와 강수와의 관계를 파악하였다. 섬 전체가 산악지형인 제주도의 연평균강수량과 지수홍수법으로 산출한 확률강우량을 강수자료로 사용하여 산악효과를 야기하는 지형인자로 선정한 고도, 위 경도와 회귀모형을 구성하였다. 회귀분석 결과 연평균강수량과 고도와의 선형관계가 확률강우량에서도 동일하게 나타났으며, 고도이외에 위도, 경도를 각각 추가인자로 고려할 경우 강우량과 더욱 강한 상관성을 보였다. 또한,

본 연구는 저수량 지역 빈도분석(regional low flow frequency analysis)을 수행하기 위하여 일반최소자승법(ordinary least squares method)을 이용한 Bayesian 다중회귀분석을 적용하였으며, 불확실성측면에서의 효과를 탐색하기 위하여 Bayesian 다중회귀분석에 의한 추정치와 t 분포를 이용하여 산정한 일반 다중회귀분석의 추정치의 신뢰구간을 비교분석하였다. 각 재현기간별 비교결과를 보면 t 분포를 이용하

겨울철에 금강하류에서는 암모니아성 질소(NH3-N) 농도가 주기적으로 높게 검출되어, 부여지점에서 취수하는 정수장의 수처리 공정에 큰 장애가 되고 있다. 질소농도 저하와 소독부산물 생성 억제를 위해 종종 대청댐의 추가 방류가 검토되고 있으나, 방류량과 직소농도 관계의 정량적 분석에 어려움이 있었다. 본 연구에서는 8년간의 일별 수질자료와 댐 방류량 자료를 이용하여 겨울철(12월∼3월) 동안 일별 NH3-N 농도를 예측할 수 있는 다중회귀모형을 개발하고,

Air quality monitoring data and meteorology data which had collected from 1995. 1. to 1999. 2. in six areas of Daegu, Manchondong, Bokhyundong, Deamyungdong, Samdukdong, Leehyundong and Nowondong, were investigated to determine the distribution and characteristic of ozone. A equation of multiple regression was suggested after time series analysis of contribution factor and meteorology factor were investigated during the day which had high concentration of ozone. The results show the following; First, 63.6% of high ozone concentration days, more than 60 ppb of ozone concentration, were in May, June and September. The percentage of each area showed that; Manchondong 14.4%, Bokhyundong 15.4%, Deamyungdong 15.6%, Samdukdong 15.6%, Leehyundong 17.3% and Nowondong 21.6%. Second, correlation coefficients of ozone, SO2, TSP, NO2 and CO showed negative relationship; the results were respectively -0.229, -0.074, -0.387, -0.190(p<0.01), and humidity were -0.677. but temperature, amount of radiation and wind speed had positive relationship; the results were respectively 0.515, 0.509, 0.400(p<0.01). Third, R2 of equation of multiple regression at each area showed that; Nowondong 45.4%, Lee hyundong 77.9%, Samdukdong 69.9%, Daemyungdong 78.8%, Manchondong 88.6%, Bokhyundong 77.6%. Including 1 hour prior ozone concentration, R2 of each area was significantly increased; Nowondong 75.2%, Leehyundong 89.3%, Samdukdong 86.4%, Daemyungdong 88.6%, Manchondong 88.6%, Bokhyundong 88.0%. Using equation of multiple regression, There were some different R2 between predicted value and observed value; Nowondong 48%, Leehyundong 77.5%, Samdukdong 58%, Daemyungdong 73.4%, Manchondong 77.7%, Bokhyundong 75.1%. R2 of model including 1 hour prior ozone concentration was higher than equation of current day; Nowondong 82.5%, Leehyundong 88.3%, Samdukdong 80.7%, Daemyungdong 82.4%, Manchondong 87.6%, Bokhyundong 88.5%.

Statistical SO_2 forecasting technique by multiple regression analysis was designed and developed to predict SO_2 concentration in Wonju City. SO_2 concentration data measured from air pollution monitoring system and meteorological factors data such as : wind speed, atmospheric stability, surface temperature, relative humidity and precipitation were used in Wonju City during the 1996∼1997. As the results, correlation model for forecasting was well fitted with some parameters including minimum temperature, wind speed and the SO_2 concentration of the previous day.

In rural planning, the cost estimation of project is a key factor for planning. Therefore, development of reliable cost estimation method is essential. Recently, new techniques are suggested for determination of project cost using historical cost data. In this study, a multiple-regression analysis was used to determine the cost of the farm land consolidation. The results demonstrated that multiple regression analysis using historical cost data can be applicable to project cost estimation.