• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.85.3-85
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• 2001

The field of forecasting is considered as an application of time-series analysis even if the data is linear or nonlinear. To obtain the forecasted values from observed data exerts a big influence on the decision-making support system or the control of machine etc. The nonlinear data appear as the random enumerated data. However we sometimes find that the pattern of past appearance repeats itself when we try to observe these data locally. From this point of view, we propose a way of forecasting nonlinear data from the pattern of past appearance using fuzzy theory. The advantages of the method are that we can forecast the next data by small numbers of previous data, and react to some differences, considering the ambiguous mature of the given data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6613-6620
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• 2014

In this paper, 228 cooperations supported by government were surveyed on the cognition levels of 5 factors for successful policies that support small business cooperation. Goal importance, awareness stage of importance, and current concerning level were scored to each question of factors. Using the results of previous studies, the maturity of each success factor, and the forecast time to mature and maturity of each question were analyzed. The results were compared with the results of a study precedent. Moreover, the changes in the participants' recognition levels were reviewed between before and after government's support. These comparative studies reflect government policies. Despite the government's supporting policies aided on building cooperation positively, the participants still worry about the decreasing government support. To allay these concerns, government policies should be implemented continuously to promote cooperation rather than a one-time support.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.161-164
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• 2006

The sales of consumer durables are composed of first time purchases and replacement purchases. Since the sales for most mature durable products are dominated by replacement sales, it is necessary to develop a model incorporating replacement component of sales in order to forecast total sales accurately. Several single product diffusion models incorporating replacement demand have been developed, but research addressing the multi-product diffusion models has not considered replacement sales. In this paper, we propose a model based on consumer choice behavior that simultaneously captures the diffusion and the replacement process for multi-product relationships. The proposed model enables the division of replacement sales into repurchase by previous users and transition purchase by users of different products. As a result, the model allows the partitioning of the total sales according to the customer groups (first-time buyers, repurchase buyers, and transition buyers), which allows companies to develop their production and marketing plans based on their customer mix. We apply the proposed model to the Korean automobile market, and compare the fitting and forecasting performance with other Bass-type multi-product models.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.117-120
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• 2006

Heavy rainfall events are occurred exceedingly various forms by a complex interaction between synoptic, dynamic and atmospheric stability. As the results, quantitative precipitation forecast is extraordinary difficult because it happens locally in a short time and has a strong spatial and temporal variations. GOES-9 imagery data provides continuous observations of the clouds in time and space at the right resolution. In this study, an power-law type algorithm(KAE: Korea auto estimator) for estimating rainfall based on the rainfall type was developed using geostationary meteorological satellite data. GOES-9 imagery and automatic weather station(AWS) measurements data were used for the classification of rainfall types and the development of estimation algorithm. Subjective and objective classification of rainfall types using GOES-9 imagery data and AWS measurements data showed that most of heavy rainfalls are occurred by the convective and mired type. Statistical analysis between AWS rainfall and GOES-IR data according to the rainfall types showed that estimation of rainfall amount using satellite data could be possible only for the convective and mixed type rainfall. The quality of KAE in estimating the rainfall amount and rainfall area is similar or slightly superior to the National Environmental Satellite Data and Information Service's auto-estimator(NESDIS AE), especially for the multi cell convective and mixed type heavy rainfalls. Also the high estimated level is denoted on the mature stage as well as decaying stages of rainfall system.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.205-211
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• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Horticultural Science & Technology
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• v.32 no.3
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• pp.303-309
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• 2014

The purpose of this study is to suggest indicators and proper standards to forecast the sensory quality of 'Hongisul' grape. Further, this study determines the optimum fruit load of 'Hongisul' grape reflecting consumer preference. Among several quality attributes, identified through instrumental and sensory evaluation, soluble solid-acid ratio was the most useful indicator of consumer preference for 'Hongisul' grapes. The ideal soluble solid-acid ratio for marketable grapes was found to be higher than 86.3. Analysis on the effects of fruit load control on fruit quality revealed a negative correlation where the latter increased as the former decreased. This trend is common for all grape species. The field with a fruit load of $1,400kg{\cdot}10a^{-1}$ exhibited a soluble solid-acid ratio of less than 86.3, uneven coloring and slow softening texture at the mature stage. However, fruit quality proved excellent in the field with a fruit load of $1,200kg{\cdot}10a^{-1}$ or less. It is therefore proposed that fruit load should be controlled to $1,200kg{\cdot}10a^{-1}$ or less when growing 'Hongisul' grapes to produce high quality grapes. We believe that this result can be used as a standard in judging harvest time and evaluating fruit quality.