• Title/Summary/Keyword: Demand forecast

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Daily Gas Demand Forecast Using Functional Principal Component Analysis (함수 주성분 분석을 이용한 일별 도시가스 수요 예측)

  • Choi, Yongok;Park, Haeseong
    • Environmental and Resource Economics Review
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    • v.29 no.4
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    • pp.419-442
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    • 2020
  • The majority of the natural gas demand in South Korea is mainly determined by the heating demand. Accordingly, there is a distinct seasonality in which the gas demand increases in winter and decreases in summer. Moreover, the degree of sensitiveness to temperature on gas demand has changed over time. This study firstly introduces changing temperature response function (TRF) to capture effects of changing seasonality. The temperature effect (TE), estimated by integrating temperature response function with daily temperature density, represents for the amount of gas demand change due to variation of temperature distribution. Also, this study presents an innovative way in forecasting daily temperature density by employing functional principal component analysis based on daily max/min temperature forecasts for the five big cities in Korea. The forecast errors of the temperature density and gas demand are decreased by 50% and 80% respectively if we use the proposed forecasted density rather than the average daily temperature density.

A study on the design of customized coastal weather contents based on the demand survey with coastal industry fields (연안산업 분야별 수요조사를 통한 맞춤형 연안기상 콘텐츠 설계방안 연구)

  • Kim, Hyunsu;Kim, Yoo-Keun;Song, Sang-Keun;Jeong, Ju-Hee;Son, Go-Eun;Kim, Dong-Sik;Kim, Hyung-Sop;Kim, Ji-Won
    • Journal of Environmental Science International
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    • v.22 no.4
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    • pp.481-492
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    • 2013
  • In this study, the use survey of domestic and international weather information on coastal regions and the demand survey (e.g. general and in-depth surveys) for customer needs with coastal industries were carried out to design customized coastal weather contents. The general demand survey showed that most of the customers working in the coastal industries were interested in a short-term forecast, such as a general weather outlook (approximately 29% of the total respondents) and typhoon information (19%), and they preferred to be given the forecast information from new media such as the internet web-pages (36%) and mobile utilities (23%) rather than old media such as TV (16%) and radio (11%). In addition, only 31% of the total respondents were found to be satisfied with the use of the current coastal weather service. This low percentage might mainly be a result of lack of information accuracy (about 64%) and diversity (28%). From in-depth survey with site visiting, the need of coastal weather contents, such as weather elements, data form, a tool of communication, and forecast interval, differed with the working stages in three coastal industries (e.g. shipbuilding, maritime trade, and passenger transport industries).

A Regression based Unconstraining Demand Method in Revenue Management (수입관리에서 회귀모형 기반 수요 복원 방법)

  • Lee, JaeJune;Lee, Woojoo;Kim, Junghwan
    • The Korean Journal of Applied Statistics
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    • v.28 no.3
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    • pp.467-475
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    • 2015
  • Accurate demand forecasting is a crucial component in revenue management(RM). The booking data of departed flights is used to forecast the demand for future departing flights; however, some booking requests that were denied were omitted in the departed flights data. Denied booking requests can be interpreted as censored in statistics. Thus, unconstraining demand is an important issue to forecast the true demands of future flights. Several unconstraining methods have been introduced and a method based on expectation maximization is considered superior. In this study, we propose a new unconstraining method based on a regression model that can entertain such censored data. Through a simulation study, the performance of the proposed method was evaluated with two representative unconstraining methods widely used in RM.

A Study on Simultaneous Load Factor of Intelligent Electric Power Reduction System in Korea (한국의 지능형 전력동시부하율 저감시스템에 관한 연구)

  • Kim, Tae-Sung;Lee, Jong-Hwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.1
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    • pp.24-31
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    • 2012
  • This study is designed to predict the overall electric power load, to apply the method of time sharing and to reduce simultaneous load factor of electric power when authorized by user entering demand plans and using schedules into the user's interface for a certain period of time. This is about smart grid, which reduces electric power load through simultaneous load factor of electric power reduction system supervision agent. Also, this study has the following characteristics. First, it is the user interface which enables authorized users to enter and send/receive such data as demand plan and using schedule for a certain period of time. Second, it is the database server, which collects, classifies, analyzes, saves and manages demand forecast data for a certain period of time. Third, is the simultaneous load factor of electric power control agent, which controls usage of electric power by getting control signal, which is intended to reduce the simultaneous load factor of electric power by the use of the time sharing control system, form the user interface, which also integrate and compare the data which were gained from the interface and the demand forecast data of the certain period of time.

A Study on the Demand Forecasting for IMT-2000 Services (IMT-2000 서비스의 수요예측)

  • Im, Su Deok;Jo, Jung Jae;Hwang, Jin Su;Jo, Yong Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.12A
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    • pp.2025-2033
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    • 1999
  • In this paper, we forecast launching time of the commercial IMT-2000 service as feb. 2001, according to expert’s opinion, and most of they forecast rapid evolution. And, we propose two different models according to two cases for competition power of price for IMT-2000 service subscriber demand forecasting. In this paper, we combine the expert’s opinion method with the growth curve model for demand forecasting for new products in order to reduce error of the demand forecasting that haven’t past references. The estimation of needed coefficients for each growth curve model is based on experts’ subjective opinions.

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A Study on the Improvement of Aircraft Contract Maintenance System (항공장비 외주정비체계 개선방안 연구)

  • Suh Sung-chul;Park Seung-hwan
    • Journal of the military operations research society of Korea
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    • v.30 no.2
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    • pp.96-107
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    • 2004
  • This paper deals with $\ulcorner$Requirement Decision Model for Repair Parts supplied by the Government$\lrcorner$ which is to reduce Aircraft Contract Maintenance Cost. It aims to find solutions to the fundamental problems of the Aircraft Contract Maintenance System. Under the current Aircraft Contract Maintenance System, it is hard to forecast the exact demand of repair parts, so support rate of Repair Parts supplied by the Government is restricted under 50 percent. It is inevitable to purchase Repair Parts from the firm with much higher price than those of Government source. However, absence of fixed demand pattern makes it difficult to improve accuracy of demand forecast. As a solution to these problems, this model prevents a cost increase due to the unit price difference between Repair Parts supplied by the Government and Repair Parts purchased by the Firm. It also reflects demand characteristics of each repair part, and prevents continual stock increase by setting an upper limit on the amount of Repair Parts supplied by the Government. The effectiveness of this model is verified by empirical analysis using the latest raw data. By applying this model to real situation, we expect to reduce about 4 billion won every year.

The Simulation and Forecast Model for Human Resources of Semiconductor Wafer Fab Operation

  • Tzeng, Gwo-Hshiung;Chang, Chun-Yen;Lo, Mei-Chen
    • Industrial Engineering and Management Systems
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    • v.4 no.1
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    • pp.47-53
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    • 2005
  • The efficiency of fabrication (fab) operation is one of the key factors in order for a semiconductor manufacturing company to stay competitive. Optimization of manpower and forecasting manpower needs in a modern fab is an essential part of the future strategic planing and a very important to the operational efficiency. As the semiconductor manufacturing technology has entered the 8-inch wafer era, the complexity of fab operation increases with the increase of wafer size. The wafer handling method has evolved from manual mode in 6-inch wafer fab to semi-automated or fully automated factory in 8-inch and 12-inch wafer fab. The distribution of manpower requirement in each specialty varied as the trend of fab operation goes for downsizing manpower with automation and outsourcing maintenance work. This paper is to study the specialty distribution of manpower from the requirement in a typical 6-inch, 8-inch to 12-inch wafer fab. The human resource planning in today’s fab operation shall consider many factors, which include the stability of technical talents. This empirical study mainly focuses on the human resource planning, the manpower distribution of specialty structure and the forecast model of internal demand/supply in current semiconductor manufacturing company. Considering the market fluctuation with the demand of varied products and the advance in process technology, the study is to design a headcount forecast model based on current manpower planning for direct labour (DL) and indirect labour (IDL) in Taiwan’s fab. The model can be used to forecast the future manpower requirement on each specialty for the strategic planning of human resource to serve the development of the industry.

Study on the Long-Term Demand Projections for Timber in Korea (우리나라 목재수요(木材需要)의 장기여측에(長期予測) 관(関)한 연구(硏究))

  • Kim, Jang Soo;Park, Ho Tak
    • Journal of Korean Society of Forest Science
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    • v.50 no.1
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    • pp.29-35
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    • 1980
  • The purpose of this study is to analyze and to forecast the long-term domestic demand and export demand for timber in Korea by regression models with time series data during 1962~1978. The method applied in this study was econometric analysis using Time Series Processor. The most important explanatory variables of timber demand were found to be the production activities of wood products industries to the prices of substitute goods. On the basis of the long-term forecast made according to the guidelines of the Fifth Five-Year Plan. According to the projection, domestic timber demand is projected at 8 million cubic meters in 1987 and 10.6 million cubic meters in 1991. On the other hand, the total demand (domestic demand plus export demand) for timber is projected 21.4 million cubic meters in 1987 and 27.2 million cubic meters in 1991.

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Probabilistic Forecasting of Seasonal Inflow to Reservoir (계절별 저수지 유입량의 확률예측)

  • Kang, Jaewon
    • Journal of Environmental Science International
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    • v.22 no.8
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    • pp.965-977
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    • 2013
  • Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

Forecasting the Demand and Supply and Diagnosing the Shortage of Marine Officer for Korean Coastal Shipping (내항 해기사 인력 수요 및 공급 예측과 인력 부족 진단)

  • Shin, Sang-Hoon;Shin, Yong-John
    • Journal of Korea Port Economic Association
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    • v.40 no.1
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    • pp.15-30
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    • 2024
  • This study examined the current status of the number of ships and marine officers in the coastal shipping in order to successfully solve the problem of the shortage of manpower. Then it forecast the number of costal ships by ship size and the demand of coastal marine officers by applying the crew quota of the Ship Personnel Act. In addition, The supply of manpower was predicted using the Markov model, reflecting the number of turnover and retirements by year, as well as the number of new entrants and incomer from ocean-going shipping. As a result of forecasts, the demand for coastal marine officers is forecast to increase from 6,057 in 2023 to 7,079 in 2030, and the supply is forecast to decrease from 5,771 in 2023 to 5,130 in 2030, showing that the manpower of shortage is worsening. This study analyzed the problem of the shortage of lower-level licensed coastal marine officers and objectively forecast the demand and supply of manpower through quantitative analysis. In order to resolve the manpower shortage, it was proposed to expand the training and supply of 5th and 6th grade low-level licensed coastal marine officers. This study will be able to provide useful data to solve the problem of shortage of manpower for coastal shipping.