• 제목/요약/키워드: Monthly forecasting

검색결과 185건 처리시간 0.023초

Monthly Hanwoo supply and forecasting models

  • Hyungwoo, Lee;Seonu, Ji;Tongjoo, Suh
    • 농업과학연구
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    • 제48권4호
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    • pp.797-806
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    • 2021
  • As the number of scaled-up ranches increased and agile responses to market changes became possible, decision-making by Hanwoo cattle farms also began to affect short-term shipments. Considering the changing environment of the Hanwoo supply market and the response speed of producers, it is necessary quickly to grasp the forecast ahead of time and to respond accordingly in an effort to stabilize supply and demand in the Hanwoo market. In this study, short-term forecasting model centered on the supply of Hanwoo was established. The analysis conducted here indicates that the slaughter of Hanwoo males increases by 0.248 as the number of beef cattle raised over 29 months of age in the previous month increases by one, and 0.764 Hanwoo females were slaughtered under average conditions for every Hanwoo male slaughtered. With regard to time, the slaughtering of Hanwoo was higher in January and August, which are months known for holiday food preparation activities for the New Year and Chuseok in Korea, respectively. Simulations indicated that errors were within 10% in all simulations performed through the Hanwoo supply model. Accordingly, it is considered that the estimation results from the supply model devised in this study are reliable and that the model has good structural stability.

계절 아리마 모형을 이용한 관광객 예측 -경북 영덕지역을 대상으로- (Forecasting of Yeongdeok Tourist by Seasonal ARIMA Model)

  • 손은호;박덕병
    • 농촌지도와개발
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    • 제19권2호
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    • pp.301-320
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    • 2012
  • The study uses a seasonal ARIMA model to forecast the number of tourists of Yeongdeok in an uni-variable time series. The monthly data for time series were collected ranging from 2006 to 2011 with some variation between on-season and off-season tourists in Yeongdeok county. A total of 72 observations were used for data analysis. The forecast multiplicative seasonal ARIMA(1,0,0)$(0,1,1)_{12}$ model was found the most appropriate one. Results showed that the number of tourists was 10,974 thousands in 2012 and 13,465 thousands in 2013, It was suggested that the grasping forecast model is very important in respect of how experts in tourism development in Yeongdeok county, policy makers or planners would establish strategies to allocate service in Yeongdeok tourist destination and provide tourism facilities efficiently.

시스템다이내믹스기법을 이용한 우리나라 양식넙치시장의 수급구조 분석 (Analyzing the Supply and Demand Structure of the Korean Flatfish Aquaculture Market : A System Dynamics Approach)

  • 박병인
    • 수산경영론집
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    • 제39권1호
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    • pp.17-42
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    • 2008
  • This study tried to build a structure model for the Korean flatfish aquaculture market by a system dynamics approach. A pool of several factors to influence the market structure was built. In addition, several reasonable factors related to the flatfish aquaculture market were selected to construct the causal loop diagram (CLD). Then the related stock/flow diagrams of the causal loop diagrams were constructed. This study had been forecasting a production price and supply, demand, and consumption volume for the flatfish market by a monthly basis, and then made some validation to the forecasting. Finally, four governmental policies such as import, storage, reduction of input, and demand control were tentatively evaluated by the created model. As a result, the facts that the demand control policy is most effective, and import and storage policies are moderately effective were found.

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Optimal Electric Energy Subscription Policy for Multiple Plants with Uncertain Demand

  • Nilrangsee, Puvarin;Bohez, Erik L.J.
    • Industrial Engineering and Management Systems
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    • 제6권2호
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    • pp.106-118
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    • 2007
  • This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

실시간 물 관리 운영을 위한 유역 유출 모의 모형 개발 (Development of Basin-wide runoff Analysis Model for Integrated Real-time Water Management)

  • 황만하;맹승진;고익환;박정인;류소라
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2003년도 학술발표논문집
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    • pp.507-510
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    • 2003
  • The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. A short-term water demand forecasting technology will be developed taking into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

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ARIMA 모형과 인공신경망모형의 BOD예측력 비교 (Comparison of the BOD Forecasting Ability of the ARIMA model and the Artificial Neural Network Model)

  • 정효준;이홍근
    • 한국환경보건학회지
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    • 제28권3호
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    • pp.19-25
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    • 2002
  • In this paper, the water quality forecast was performed on the BOD of the Chungju Dam using the ARIMA model, which is a nonlinear statistics model, and the artificial neural network model. The monthly data of water quality were collected from 1991 to 2000. The most appropriate ARIMA model for Chungju dam was found to be the multiplicative seasonal ARIMA(1,0,1)(1,0,1)$_{12}$, model. While the artificial neural network model, which is used relatively often in recent days, forecasts new data by the strength of a learned matrix like human neurons. The BOD values were forecasted using the back-propagation algorithm of multi-layer perceptrons in this paper. Artificial neural network model was com- posed of two hidden layers and the node number of each hidden layer was designed fifteen. It was demonstrated that the ARIMA model was more appropriate in terms of changes around the overall average, but the artificial neural net-work model was more appropriate in terms of reflecting the minimum and the maximum values.s.

Forecasting of Stream Qualities at Gumi industrial complex by Winters' Exponential Smoothing

  • Song, Phil-Jun;Um, Hee-Jung;Kim, Jong-Tae
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1133-1140
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    • 2008
  • The goal of this paper is to analysis of the trend for stream quality in Gumi industrial complex with Winters' exponential smoothing method. It used the five different monthly time series data such as BOD, COD, TN, TP and EC from January 1998 to December 2006. The data of BOD, COD, TN, TP and EC are analyzed by time series method and forecasted the trends until December 2007. The stream qualities change for the better about BOD, COD, TN and TP, but the stream qualities resulted by EC is still serious.

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Mean-VaR Portfolio: An Empirical Analysis of Price Forecasting of the Shanghai and Shenzhen Stock Markets

  • Liu, Ximei;Latif, Zahid;Xiong, Daoqi;Saddozai, Sehrish Khan;Wara, Kaif Ul
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1201-1210
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    • 2019
  • Stock price is characterized as being mutable, non-linear and stochastic. These key characteristics are known to have a direct influence on the stock markets globally. Given that the stock price data often contain both linear and non-linear patterns, no single model can be adequate in modelling and predicting time series data. The autoregressive integrated moving average (ARIMA) model cannot deal with non-linear relationships, however, it provides an accurate and effective way to process autocorrelation and non-stationary data in time series forecasting. On the other hand, the neural network provides an effective prediction of non-linear sequences. As a result, in this study, we used a hybrid ARIMA and neural network model to forecast the monthly closing price of the Shanghai composite index and Shenzhen component index.

기후변화를 고려한 한반도 미래 풍력자원 지도 생산 (Production of Future Wind Resource Map under Climate Change over Korea)

  • 김진영;김도용
    • 대한공간정보학회지
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    • 제25권1호
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    • pp.3-8
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    • 2017
  • 본 연구에서는 앙상블 중규모기후모델 weather research and forecasting(WRF)를 이용하여 2045년부터 2054년까지 21세기 중반의 기후변화에 대한 우리나라 미래 풍력자원 지도를 제작하였고 월별, 시간대별 자원변화를 검토하였다. 분석결과, 한반도상에서 강한 몬순 순환으로 인해 뚜렷한 월별 시공간 변동성이 해륙풍에 의한 시간대별 변동성보다 컸다. 풍력자원이 큰 강풍지역은 월마다 지역마다 다르게 나타났다. 즉 겨울철 북서계절풍(여름철 남서계절풍)이 주풍일 때 각각 강원산간과 해상 그리고 남서해안에서 자원이 많을 것으로 전망되었다. 최대풍과 최소풍은 1월, 9월에 각각 나타날 것으로 전망되었고, 시간대별로 내륙과 산간은 일중편차가 컸지만 연안지역은 편차가 작을 것으로 전망되었다. 이는 현재기후에 대한 기존분석결과와는 다소 차이가 있는 것으로, 이 연구에서 생산된 미래 풍력자원 지도는 향후 기후 변화 가능성이 큰 지역의 시공간적 풍황을 감안하여 풍력단지 입지 선정 및 풍력운영을 위한 장기계획 마련에 있어서 유용한 자료가 되리라 기대된다.

항만경쟁력 제고를 위한 항만교역량 예측 (Forecasting the Port Trading Volumes for Improvement of Port Competitive Power)

  • 손용정
    • 한국항만경제학회지
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    • 제25권1호
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    • pp.1-14
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    • 2009
  • 항만산업의 발전은 저렴하고 효율적인 서비스 제공을 가능하게 함으로써 자국 경제발전을 지원하는 기능을 하는 동시에 독립된 산업으로 부가가치 및 고용창출을 기대할 수 있다. 그러나 국내 주요 항만들은 대내의적인 여건의 변화로 항만교역량 증가세가 둔화되고 있으며 국내 항만의 여건악화는 일시적인 현상이라기보다는 구조적인 현상이라는 점에 문제의 심각성이 있다. 즉, 향후 주요 항만들의 교역량 증가세가 회복될 가능성이 크지 않다는 것이 일반적인 견해이며, 역내 물류중심 기능을 수행할 수 있을 것인지에 대한 회의론 마저 대두되고 있는 실정이다. 항만개발에 소요되는 시간과 재원은 막대하다. 특히 신항개발의 경우 최소 10년 이상의 장기수요 전망 하에 개발계획의 수립이 이루어진다. 따라서 개발계획의 기본이 되는 교역량의 예측의 중요성은 최근 교역량과 관련한 대외적인 환경 변화에 따라 중요성이 더욱 부각되고 있다. 이처럼 산업이 고도화되고 구조도 급격히 변화되고 있는 시대 흐름에 비추어 정확한 물동량예측은 유용하게 이용될 수 있다. 따라서 본고에서는 승법계절 ARIMA모형을 이용하여 국내항만과 중국항만간의 교역량 변화를 예측해보고, 이러한 예측을 통하여 우리나라 항만의 역할과 경쟁력을 갖추기 위한 필요성이 제기됨에 따라 항만의 교역량 중대를 위한 항만활성화 방안을 제시하고자 한다.

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