• 제목/요약/키워드: Double exponential smoothing method

검색결과 13건 처리시간 0.021초

Suggesting Forecasting Methods for Dietitians at University Foodservice Operations

  • Ryu Ki-Sang
    • Nutritional Sciences
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    • 제9권3호
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    • pp.201-211
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    • 2006
  • The purpose of this study was to provide dietitians with the guidance in forecasting meal counts for a university/college foodservice facility. The forecasting methods to be analyzed were the following: naive model 1, 2, and 3; moving average, double moving average, simple exponential smoothing, double exponential smoothing, Holt's, and Winters' methods, and simple linear regression. The accuracy of the forecasting methods was measured using mean squared error and Theil's U-statistic. This study showed how to project meal counts using 10 forecasting methods for dietitians. The results of this study showed that WES was the most accurate forecasting method, followed by $na\ddot{i}ve$ 2 and naive 3 models. However, naive model 2 and 3 were recommended for using by dietitians in university/college dining facilities because of the accuracy and ease of use. In addition, the 2000 spring semester data were better than the 2000 fall semester data to forecast 2001spring semester data.

한국에서 산업재해율 예측에 의한 산업재해방지 전략에 관한 연구 (The Study on Strategy for Industrial Accident Prevention by the Industrial Accident Rate Forecasting in Korea)

  • 강영식;김태구;안광혁;최도림;정유나;이승호;박민아;이슬;김성현
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2011년도 춘계학술대회
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    • pp.177-183
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    • 2011
  • Korea has performed strategies for the third industrial accident prevention in order to minimize industrial accident. However, the occupational fatality rate and industrial accident rate appears to be stagnated for 11 years. Therefore, this paper forecasts the occupational fatality rate and industrial accident rate for 10 years. Also, this paper applies regression method (RA), exponential smoothing method (ESM), double exponential smoothing method (DESM), autoregressive integrated moving average (ARIMA) model and proposed analytical function method (PAFM) for trend of industrial accident. Finally, this paper suggests fundamental strategies for industrial accident prevention by forecasting of industrial accident rate in the long term.

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Predictive Hybrid Redundancy using Exponential Smoothing Method for Safety Critical Systems

  • Kim, Man-Ho;Lee, Suk;Lee, Kyung-Chang
    • International Journal of Control, Automation, and Systems
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    • 제6권1호
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    • pp.126-134
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    • 2008
  • As many systems depend on electronics, concern for fault tolerance is growing rapidly. For example, a car with its steering controlled by electronics and no mechanical linkage from steering wheel to front tires (steer-by-wire) should be fault tolerant because a failure can come without any warning and its effect is devastating. In order to make system fault tolerant, there has been a body of research mainly from aerospace field. This paper presents the structure of predictive hybrid redundancy that can remove most erroneous values. In addition, several numerical simulation results are given where the predictive hybrid redundancy outperforms wellknown average and median voters.

Hybrid CSA optimization with seasonal RVR in traffic flow forecasting

  • Shen, Zhangguo;Wang, Wanliang;Shen, Qing;Li, Zechao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권10호
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    • pp.4887-4907
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    • 2017
  • Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

기초자치단체의 학생수 추계를 위한 알고리즘 (The proposed algorithm for the student numbers in local government)

  • 김종태
    • Journal of the Korean Data and Information Science Society
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    • 제22권6호
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    • pp.1167-1173
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    • 2011
  • 본 연구의 목적은 기초자치단체인 시 군의 장래 학생수 추계를 위한 알고리즘을 제시하는데 있다. 인구추계를 위하여 시계열 방법의 이중지수평활법을 사용하였다. 결론적으로 2044년까지 고등학교 3학년 학생수의 경우에는 칠곡, 구미, 경산, 안동, 포항, 김천은 40%-70% 정도 줄고, 나머지 시 군은 70%-95%이상 학생이 줄며, 심지어 군위, 청송, 성주, 울릉, 의성, 영양 등 6개 군은 26년 후인 2036년에는 고등3학년 학생이 없을 것으로 추정된다. 초등1학년의 경우는 2044년까지 칠곡, 구미, 안동, 경산까지는 약 50%-70% 사이까지 줄어들고, 나머지 시 군은 70%-100% 줄어든다. 특히 군위, 의성, 성주, 청송, 청도, 울진, 고령은 2044년까지 순차적으로 초등1학년 학생이 없을 것으로 추정된다.

위성영상과 임상통계를 이용한 충남해안지역의 기후변화에 따른 임상 변화 (Changes of the Forest Types by Climate Changes using Satellite imagery and Forest Statistical Data: A case in the Chungnam Coastal Ares, Korea)

  • 김찬수;박지훈;장동호
    • 환경영향평가
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    • 제20권4호
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    • pp.523-538
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    • 2011
  • This study analyzes the changes in the surface area of each forest cover, based on temperature data analysis and satellite imagery as the basic methods for the impact assessment of climate change on regional units. Furthermore, future changes in the forest cover are predicted using the double exponential smoothing method. The results of the study have shown an overall increase in annual mean temperature in the studied region since 1990, and an especially increased rate in winter and autumn compared to other seasons. The multi-temporal analysis of the changes in the forest cover using satellite images showed a large decrease of coniferous forests, and a continual increase in deciduous forests and mixed forests. Such changes are attributed to the increase in annual mean temperature of the studied regions. The analysis of changes in the surface area of each forest cover using the statistical data displayed similar tendencies as that of the forest cover categorizing results from the satellite images. Accordingly, rapid changes in forest cover following the increase of temperature in the studied regions could be expected. The results of the study of the forest cover surface using the double exponential smoothing method predict a continual decrease in coniferous forests until 2050. On the contrary, deciduous forests and mixed forests are predicted to show continually increasing tendencies. Deciduous forests have been predicted to increase the most in the future. With these results, the data on forest cover can be usefully applied as the main index for climate change. Further qualitative results are expected to be deduced from these data in the future, compared to the analyses of the relationship between tree species of forest and climate factors.

버스정보기반 통행속도 추정에 관한 연구 (A Study on the Travel Speed Estimation Using Bus Information)

  • 빈미영;문주백;임승국
    • 한국ITS학회 논문지
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    • 제12권4호
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    • pp.1-10
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    • 2013
  • 본 연구는 버스정보가 도로의 통행속도 정보로 활용될 수 있는지를 검토하기 위한 연구이다. 도로통행속도를 파악하기 위해 설치된 지점검지기, 구간검지기로부터 수집되는 정보와 경기도에서 수집되는 버스정보를 속도정보로 가공하여 비교하였다. 버스정보가 교통정보 검지기의 기능을 할 수 있다면, 통행속도 정보를 제공할 수 있다. 이를 위해서는 도로구간의 교통류에 대한 패턴을 인식할 필요가 있다. 본 연구에서는 새로운 접근방법보다는 기존에 검증된 방법을 중심으로 버스정보를 이용한 교통류 패턴 인식 방법을 적용하여 버스정보의 활용 가능성을 제시하였다. 또한 버스정보를 이용하여 모형을 추정하였는데, 단순이동, 지수평활법과 이중이동, 이중지수평활법, ARIMA(p,d,q)모형을 적용하였다. 이 모형들은 평가지표인 100-MAPE, MAE, EC로 비교한 결과 상호 비슷한 결과를 나타냈으나, 단순평균이동법이 가장 우수한 결과를 나타냈다. 이로서 버스정보를 구간의 통행속도로 이용할 경우, 모형의 추정도 가능하다는 것을 확인하였다.

적정 진급인원수 결정 및 진급확률 민감도 분석 (Determination of the Appropriate Promotion Size and Sensitivity Analysis of Promotion Probabilities)

  • 이익주;민계료
    • 한국국방경영분석학회지
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    • 제15권2호
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    • pp.20-37
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    • 1989
  • A markov chain is used to derive the models for determining the size of persons to be promoted and for conducting the sensitivity analysis of promotion probabilities. To compute the former case a future wastage rate is forecasted by using the double exponential smoothing method. The model for sensitivity analysis is used to simulate the impact of change in graded-size targets and hiring policy on the promotion probabilities.

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건설업에서 재해율과 업무상 사고 사망의 예측 및 평가 (Forecasting and Evaluation of the Accident Rate and Fatal Accident in the Construction Industries)

  • 강영식
    • 산업경영시스템학회지
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    • 제40권1호
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    • pp.87-94
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    • 2017
  • Many industrial accidents have occurred continuously in the manufacturing industries, construction industries, and service industries of Korea. Fatal accidents have occurred most frequently in the construction industries of Korea. Especially, the trend analysis of the accident rate and fatal accident rate is very important in order to prevent industrial accidents in the construction industries systematically. This paper considers forecasting of the accident rate and fatal accident rate with static and dynamic time series analysis methods in the construction industries. Therefore, this paper describes the optimal accident rate and fatal accident rate by minimization of the sum of square errors (SSE) among regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, proposed analytic function model (PAFM), and kalman filtering model (KFM) with existing accident data in construction industries. In this paper, microsoft foundation class (MFC) soft of Visual Studio 2008 was used to predict the accident rate and fatal accident rate. Zero Accident Program developed in this paper is defined as the predicted accident rate and fatal accident rate, the zero accident target time, and the zero accident time based on the achievement probability calculated rationally and practically. The minimum value for minimizing SSE in the construction industries was found in 0.1666 and 1.4579 in the accident rate and fatal accident rate, respectively. Accordingly, RAM and ARIMA model are ideally applied in the accident rate and fatal accident rate, respectively. Finally, the trend analysis of this paper provides decisive information in order to prevent industrial accidents in construction industries very systematically.

X-By-Wire 시스템의 센서 결함 허용을 위한 Fuzzy Hybrid Redundancy 개발 (Development of Fuzzy Hybrid Redundancy for Sensor Fault-Tolerant of X-By-Wire System)

  • 김만호;손병점;이경창;이석
    • 제어로봇시스템학회논문지
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    • 제15권3호
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    • pp.337-345
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    • 2009
  • The dependence of numerous systems on electronic devices is causing rapidly increasing concern over fault tolerance because of safety issues of safety critical system. As an example, a vehicle with electronics-controlled system such as x-by-wire systems, which are replacing rigid mechanical components with dynamically configurable electronic elements, should be fault¬tolerant because a devastating failure could arise without warning. Fault-tolerant systems have been studied in detail, mainly in the field of aeronautics. As an alternative to solve these problems, this paper presents the fuzzy hybrid redundancy system that can remove most erroneous faults with fuzzy fault detection algorithm. In addition, several numerical simulation results are given where the fuzzy hybrid redundancy outperforms with general voting method.