To examine the trend on the flowering time in some weather flora including Prunus serrulata var. spontanea, Cosmos bipinnatus, and Robinia pseudo-acacia in Busan, the changes in time series and rate of flowering time of plants were analyzed using the method of time series analysis. According to the correlation between the flowering time and the temperature, changing pattern of flowering time was very similar to the pattern of the temperature, and change rate was gradually risen up as time goes on. Especially, the change rate of flowering time in C. bipinnatus was 0.487 day/year and showed the highest value. In flowering date in 2007, the difference was one day between measurement value and prediction value in C. bipinnatus and R. pseudo-acacia, whereas the difference was 8 days in P. mume showing great difference compared to other plants. Flowering time was highly related with temperature of February and March in the weather flora except for P. mume, R. pseudo-acacia and C. bipinnatus. In most plants, flowering time was highly related with a daily average temperature. However, the correlation between flowering time and a daily minimum temperature was the highest in Rhododendron mucronulatum and P. persica, otherwise the correlaton between flowering time and a daily maximum temperature was the highest in Pyrus sp.

본 논문에서는 본 연구논제(2007)에서 개발된 COMBINE-GRNNM-GA(Type-1)으로부터 최적형태의 구조를 가진 모형을 구성하고, 입력층노드의 기상인자를 제거하기 위하여 불확실성 분석을 실시하였다. 훈련과정중에 가장 최소의 평활인자를 가진 입력층변수는 COMBINE-GRNNM-GA(Type-1)에서 제거되었으며, 변형된 COMBINE-GRNNM-GA(Type-1)은 기상학적 변수의 새로운 최소 평활인자를 구하기 위하여 재훈련된다. 최소 평활인

본 연구에서는 전국 59개 지점의 3개월 SPI 자료를 가지고 EOF를 유도하고 아울러 그 공간적 특성을 분석하였다. 또한 EOF 해석에 의해 나타난 Coefficient Time Series를 다변량 시계열 모형에 적용하여 SPI 시계열을 자료기간 10,000년으로 확장하였고 전국적인 가뭄심도를 판단하기 위해 전국 평균 지수를 이용하여 재현기간별 최대심도를 결정하였다. 마지막으로 각 대권역의 댐 유효저수량과 농경지 면적을 이용하여 농업가뭄 대비능력을

본 논문은 수문시계열에서 나타나는 주기성 및 경향성 등을 평가하기 위한 방법으로 Fourier Transform을 개선한 Wavelet Transform방법을 제시하고 이에 대한 타당성 및 적용성을 월강수량 및 연강수량 자료와 대표적인 기상인자인 남방진동지수(SOI)와 해수면온도(SST)를 대상으로 평가해 보았다. Fourier Transform은 시간적인 특성을 파악하지 못하는 반면에 Wavelet Transform은 수문시계열이 갖는 시간적인 특성을

To identify possible associations with concentrations of ambient air pollutants and daily mortality in Busan, this study assessed the effects of air pollution for the time period 1999-2000. Poisson regression analysis by Generalized Additive Model were conducted considering trend, season, meteorology, and day-of-the-week as confounders in a nonparametric approach. Busan had a 10% increase in mortality in persons aged 65 and older(95% CI : 1.01-1.10) in association with IQR in NO2(lagged 2 days). An increase of NO2(lagged 2days) was associated with a 4% increase in respiratory mortality(CI : 1.02-1.11) and CO(lagged 1 day) showed a 3% increase(CI : 1.00-1.07).