• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.117-124
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• 2009

If time series data with seasonal effect exist, various statistical models like winters for successful forecasts could be used. But if the data are not enough to estimate seasonal effect, not much methods are available. This paper proposes the statistical forecasting method based on cumulative data when the data are not enough to estimate seasonal effect. We apply this method to real cosmetic sales data and show its better performance over moving average method.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.343-365
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• 2022

This paper tries to identify the effect of reducing PM2.5 concentration of the First Seasonal Management Policy implemented by Korean government by using statistical method. In particular, this paper tests the hypothesis that this policy effect may differ by region (west-coast, south-coast, and east-coast). To this end, this paper analyzed only pure policy effects by removing temporal abnormalities such as COVID-19, warm winter temperature during the policy implementation period (December 2019 to March 2020) by using the difference-in-difference method (DID). As a result of the analysis, this policy had the effect of reducing PM2.5, but the effect is not homogenous by region. In particular, PM2.5 reducing effect is the largest in west-coast region and south-coast region folllows, but its effect is not statistically significant in the east-cost region. In conclusion, this paper drew implications that the current Seasonal mamangement policy which is implemented regardless of the regional difference needs to be changed.

• Ecology and Resilient Infrastructure
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• v.5 no.3
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• pp.125-133
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• 2018

Artificial neural network (ANN) is a powerful model to predict time series data and have been frequently adopted to predict groundwater level (GWL). Many researchers have also tried to improve the performance of ANN prediction for GWL in many ways. Dummies are usually used in ANN as input to reflect the seasonal effect on predicted results, which is necessary for improving the predicting performance of ANN. In this study, the effect of Dummy on the prediction performance was analyzed qualitatively and quantitatively using several graphical methods, correlation coefficient and performance index. It was observed that results predicted using dummies for ANN model indicated worse performance than those without dummies.

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2000.05a
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• pp.218-219
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• 2000

바다목장화는 자연급이형 재배어업시스템이며, 해류제어 막구조물(Fig. 1)은 (1)어패류의 서식환경 조성 및 제공, (2)기초생산의 증대를 통한 고차 소비자의 위집과 생산 증대 및 (3)어류의 사료가 되는 저서생물의 증식 효과라는 직접적인 효과와 (4) 와류, 상승류에 수반된 유동변화, 음향발생 등에 의한 부차적인 집어효과를 가질 뿐 아니라 (5) 저층 영양염의 분산 소모를 통한 계절적 영양염의 집중부상에 의한 계절적 부영양화의 감소효과를 가지는 기능시설로서 중요한 증식시설이다(김과 류, 1997). (중략)

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.885-893
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• 2015

It is important to improve the forecasting accuracy of one-year-ahead seasonal factors in order to produce seasonally adjusted series of the following year. In this paper, seasonal factors of 8 monthly Korean economic time series are examined and forecast based on the functional principal component regression. One-year-ahead forecasts of seasonal factors from the functional principal component regression are compared with other forecasting methods based on mean absolute error (MAE) and mean absolute percentage error (MAPE). Forecasting seasonal factors via the functional principal component regression performs better than other comparable methods.

• Journal of the Korean Society of Earth Science Education
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• v.12 no.2
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• pp.151-164
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• 2019

The purpose of this study is to find out the effects of reconstructing unit 'Seasonal Change' using step-by-step questioning for concepts changes to adjusting misconceptions of elementary school students. Most students have pre-conceptions at describing seasonal changes based on their experiences. Therefore, in newly developed unit, we reconstructed unit to include core teaching and learning contents by finding out common pre-conceptions of students and specifying purpose of teaching at misconceptions found in pre-conceptions as 'constituent of class for conceptual change'. After the scientific concept test, the result of 24 students in experimental group is statistically significant. Also, according to the result of qualitative analysis, the number of activated conceptional resources and degree of specificity in explaining seasonal changes are higher than that of control group.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.306-316
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• 2007

Based on a concept of soundscape, this study aims to investigate Koreans' preference for auditory elements, features, and impressions depending upon the season, and examine how these auditory factors of soundstape and seasons interact with each other and attempt to discover their influence on people's auditory preferences. According to an environmental psychological approach called the caption evaluation method, 45 college students examined the soundscape of Namwon City while racing the streets in four seasons. In order to analyze the interactions between seasons and such auditory factors as elements, features, and impressions, it was conducted the GLM univariate analysis and the NPAR tests for independent samples. The results of the analyses show that there are interactive effects between seasons and auditory factors like elements, features, and impressions and that the auditory factors have an effect on auditory preference. Moreover, as for seasonal preference for auditory elements, it was found that people prefer natural sound in spring, summer, and fall while they prefer social sound in winter. Concerning seasonal preference for auditory features, people place a focus on the behaviors in spring, summer, and winter while they stress the surroundings in autumn, as for seasonal preference for auditory impressions, they make much of sound characteristics in spring and winter but they value the atmosphere of streets in summer and fall. The results of this study can he utilized as useful data in determining which auditory factors among elements, features, and impressions to take into consideration in a soundscape design.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.93-102
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• 2011

In this paper, we compared the performance of the several time series models for tourism demand forecasting. We showed that seasonal effects in the data(Japan, China, USA, and Philippines) exist in the tourism data and the forecasting accuracies are compared by the RMSE criterion.

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.69-83
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• 1996

본 논문에서는 날씨가 좋은 날의 주식수익률이 날씨가 나쁜 날의 주식수익률보다 높다는 이른 바 날씨효과가 우리나라 주식시장에 존재하는 지의 여부를 검증하였다. 본 논문에서 발견된 실증분석 결과는 다음과 같이 요약될 수 있다. 첫째, 날씨가 좋은 날과 날씨가 궂은 날의 주식수익률의 차이분석에서는 전체표본기간동안 날씨효과가 존재하였다. 그러나, 주식시장 장세별로 보면 날씨효과는 주가변동성이 높은 상승기와 침체기에 나타났을 뿐, 주가변동이 낮은 안정기와 회복기에는 나타나지 않았다. 둘째, 비동시거래효과, 계절효과, 그리고 요일효과 등을 통제하고 순수하게 날씨 효과만을 검증한 회귀분석에서도 차이분석에서 보다 미약하지만 날씨효과가 존재하였으며, 이는 상승기에 집중되었다. 본 논문에서 발견된 실증분석 결과는 우리나라 주식시장의 정보적 효율성을 기각하는 새로운 증거로 해석될 수 있으며, 주식투자자들의 효율적 투자전략 수립에 의미있는 시사점을 제공할 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.56-65
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• 2019

This study empirically analyzes the effect of weather on pedestrian volume in an urban space. We used data from the 2009 Seoul Flow Population Survey and constructed a model with the pedestrian volume as a dependent variable and the weather and physical environment as independent variables. We constructed 28 models and compared the results to determine the effects of weather on pedestrian volume by season, land use, and time zone. A negative binomial regression model was used because the dependent variable did not have a normal distribution. The results show that weather affects the volume of walking. Rain reduced walking volume in most models, and snow and thunderstorms reduced the volume in a small number of models. The effects of the weather depended on the season and land use, and the effects of environmental factors depended on the season. The results have various policy implications. First, it is necessary to provide semi-outdoor urban spaces that can cope with snow or rain. Second, it is necessary to have different policies to encourage walking for each season.