• Journal of Fashion Business
• /
• v.15 no.6
• /
• pp.176-203
• /
• 2011

In today's intensifying global competition, Korean fashion industry is relying on only qualitative data for feasibility study of future projects and developmental plan. This study was conducted in order to support establishment of a scientific and rational management system that reflects market demand. First, fashion market size was limited to the total amount of expenditure for fashion clothing products directly purchased by Koreans for wear during 6 months in spring and summer and 6 months in autumn and winter. Fashion market forecasting model was developed using statistical forecasting method proposed by previous research. Specifically, time series model was selected, which is a verified statistical forecasting method that can predict future demand when data from the past is available. The time series for empirical analysis was fashion market sizes for 8 segmented markets at 22 time points, obtained twice each year by the author from 1998 to 2008. Targets of the demand forecasting model were 21 research models: total of 7 markets (excluding outerwear market which is sensitive to seasonal index), including 6 segmented markets (men's formal wear, women's formal wear, casual wear, sportswear, underwear, and children's wear) and the total market, and these markets were divided in time into the first half, the second half, and the whole year. To develop demand forecasting model, time series of the 21 research targets were used to develop univariate time series models using 9 types of exponential smoothing methods. The forecasting models predicted the demands in most fashion markets to grow, but demand for women's formal wear market was forecasted to decrease. Decrease in demand for women's formal wear market has been pronounced since 2002 when casualization of fashion market intensified, and this trend was analyzed to continue affecting the demand in the future.

• ETRI Journal
• /
• v.41 no.2
• /
• pp.224-234
• /
• 2019

This paper proposes a new spectrum forecasting (SF) model to estimate the spectrum demands for future mobile broadband (MBB) services. The model requires five main input metrics, that is, the current available spectrum, site number growth, mobile data traffic growth, average network utilization, and spectrum efficiency growth. Using the proposed SF model, the future MBB spectrum demand for Malaysia in 2020 is forecasted based on the input market data of four major mobile telecommunication operators represented by A-D, which account for approximately 95% of the local mobile market share. Statistical data to generate the five input metrics were obtained from prominent agencies, such as the Malaysian Communications and Multimedia Commission, OpenSignal, Analysys Mason, GSMA, and Huawei. Our forecasting results indicate that by 2020, Malaysia would require approximately 307 MHz of additional spectrum to fulfill the enormous increase in mobile broadband data demands.

• Convergence Security Journal
• /
• v.6 no.4
• /
• pp.121-132
• /
• 2006

Every country of the world have made their desirable future by improving the methodology of technology forecasting with priority, selection and concentration, despite the limited budget. About 20 years have passed since Defense S&T forecasting has been initiated but supplier-centered technology forecasting has caused the lack of usefulness for the customers. Therefore, we will search and offer technologies that customers need, based on the methodology of technology foresight that has started in England. It is a real value of Defense S&T forecasting that will help our nation, a smaller and weaker country compared to our neighboring countries, has a secure future and prosperity. For this consideration, 8 directions of the development for Defense S&T forecasting are suggested.

• Science of Emotion and Sensibility
• /
• v.17 no.3
• /
• pp.83-94
• /
• 2014

The present study examined the intensity of affective forecasting and the size of affective forecasting errors of people who experienced social exclusion or those high in need to belong. In Particular, a series of studies was designed to explore the moderating role of the types of future events (i.e. social vs. non-social events) in the relationship between social exclusion, the need to belong and affective forecasting. Results indicated that participants who experienced social exclusion or be high in need to belong showed significantly extreme affective ratings on the future social events compared to the future non-social events. Additional results suggested that more social exclusion experiences or higher needs to belong did not affect to the affective ratings on the experienced social events, indicating greater affective forecasting errors of socially excluded people or people with higher need to belong. The implications and limitations of the results were also discussed.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.5
• /
• pp.2057-2067
• /
• 2013

Traffic demand forecasting for pavement management in the present can be estimated using the past trends or subjective judgement of experts instead of objective methods. Also future road plans and local development plans of a target region, for example new road constructions and detour plans cannot be considered for the estimate of future traffic demands. This study, which is the fundamental research for developing objective and accurate decision-making support system of maintenance management for the national highway, proposed the methodology to predict future traffic demands according to 4-step traffic forecasting method using EMME in order to examine significance of future traffic demands affecting pavement deterioration trends and compare existing traffic demand forecasting methods. For the case study, this study conducted the comparison of traffic demand forecasting methods targeting Daejeon Regional Construction and Management Administration. Therefore, this study figured out that the differences of traffic demands and the level of agent costs as well as user costs between existing traffic demand forecasting methods and proposed traffic demand forecasting method with considering future road plans and local development plan.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.6B
• /
• pp.1120-1126
• /
• 2000

Recently, in order to analyze the time series problems that occur in the nature word, and analyzing method using a neural electric network is being studied more than a typical statistical analysis method. A neural electric network has a generalization performance that is possible to estimate and analyze about non-learning data through the learning of a population. In this paper, after collecting weather datum that was collected from 1987 to 1996 and learning a population established, it suggests the weather forecasting system for an estimation and analysis the future weather. The suggested weather forecasting system uses 28*30*1 neural network structure, raises the total learning numbers and accuracy letting the selecting concentration learning about the pattern, that is not collected, using the descending epsilon learning method. Also, the weather forecasting system, that is suggested through a comparative experiment of the typical time series analysis method shows more superior than the existing statistical analysis method in the part of future estimation capacity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2013.11a
• /
• pp.46-47
• /
• 2013

In the satellite system design, the processes from the initial design to launch take about 5 years and the broadcasting satellite lifetime goes over 15 years. Furthermore, global warming phenomenon causes rainfall rate increasing more and more in some regions on the earth. Consequently, at the stage of the satellite link design, we need to consider the future rain attenuation over 20 years. In this paper, we investigated two time-series system models for forecasting to consider the future rainfall rate for the satellite broadcasting service. We found that rainfall rate of the future 30 years is increasing continuously.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 1998.04a
• /
• pp.56-57
• /
• 1998

• Journal of Korean Society for Quality Management
• /
• v.9 no.2
• /
• pp.2-9
• /
• 1981

This paper deals with the critical role when adjustments of the regression model parameters play in forecasting. It attempts to formulate a methodology or systematic procedure for (1) detecting the points of adjustments and (2) finding the adjusted regression model parameters. The paper shows how the information of past experience in forecasting can be used future forecasting.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2007.05a
• /
• pp.397-399
• /
• 2007

This paper presents multiple regression analysis and data update to improve present spatial electric load forecasting algorithm of the DISPLAN. Spatial electric load forecasting considers a local economy, the number of local population and load characteristics. A Case study is performed for Jeon-Ju and analyzes a trend of the spatial load for the future 20 years. The forecasted information can contribute to an asset management of distribution systems.