• Atmosphere
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• v.28 no.3
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• pp.291-303
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• 2018

In this study, a new consensus technique for predicting tropical cyclone (TC) intensity in the western North Pacific was developed. The most important feature of the present consensus model is to select and combine the guidance numerical models with the best performance in the previous years based on various evaluation criteria and averaging methods. Specifically, the performance of the guidance models was evaluated using both the mean absolute error and the correlation coefficient for each forecast lead time, and the number of the numerical models used for the consensus model was not fixed. In averaging multiple models, both simple and weighted methods are used. These approaches are important because that the performance of the available guidance models differs according to forecast lead time and is changing every year. In particular, this study develops both a multi-consensus model (M-CON), which constructs the best consensus models with the lowest error for each forecast lead time, and a single best consensus model (S-CON) having the lowest 72-hour cumulative mean error, through on training process. The evaluation results of the selected consensus models for the training and forecast periods reveal that the M-CON and S-CON outperform the individual best-performance guidance models. In particular, the M-CON showed the best overall performance, having advantages in the early stages of prediction. This study finally suggests that forecaster needs to use the latest evaluation results of the guidance models every year rather than rely on the well-known accuracy of models for a long time to reduce prediction error.

• Atmosphere
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• v.25 no.2
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• pp.375-387
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• 2015

A Selected Multi-model CONsensus (SMCON) technique was developed and verified for the tropical cyclone track forecast in the western North Pacific. The SMCON forecasts were produced by averaging numerical model forecasts showing low 70% latest 6 h prediction errors among 21 models. In the homogeneous comparison for 54 tropical cyclones in 2013 and 2014, the SMCON improvement rate was higher than the other forecasts such as the Non-Selected Multi-model CONsensus (NSMCON) and other numerical models (i.e., GDAPS, GEPS, GFS, HWRF, ECMWF, ECMWF_H, ECMWF_EPS, JGSM, TEPS). However, the SMCON showed lower or similar improvement rate than a few forecasts including ECMWF_EPS forecasts at 96 h in 2013 and at 72 h in 2014 and the TEPS forecast at 120 h in 2013. Mean track errors of the SMCON for two year were smaller than the NSMCON and these differences were 0.4, 1.2, 5.9, 12.9, 8.2 km at 24-, 48-, 72-, 96-, 120-h respectively. The SMCON error distributions showed smaller central tendency than the NSMCON's except 72-, 96-h forecasts in 2013. Similarly, the density for smaller track errors of the SMCON was higher than the NSMCON's except at 72-, 96-h forecast in 2013 in the kernel density estimation analysis. In addition, the NSMCON has lager range of errors above the third quantile and larger standard deviation than the SMCON's at 72-, 96-h forecasts in 2013. Also, the SMCON showed smaller bias than ECMWF_H for the cross track bias. Thus, we concluded that the SMCON could provide more reliable information on the tropical cyclone track forecast by reflecting the real-time performance of the numerical models.

• Atmosphere
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• v.21 no.2
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• pp.209-220
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• 2011

A new consensus algorithm for the prediction of tropical cyclone track has been developed. Conventional consensus is a simple average of a few fixed models that showed the good performance in track prediction for the past few years. Meanwhile, the consensus in this study is a weighted average of a few models that may change for every individual forecast time. The models are selected as follows. The first step is to find the analogous past tropical cyclone tracks to the current track. The next step is to evaluate the model performances for those past tracks. Finally, we take the weighted average of the selected models. More weight is given to the higher performance model. This new algorithm has been named as DYTRAP (DYnamic data-base Typhoon tRAck Prediction) in the sense that the data base is used to find the analogous past tracks and the effective models for every individual track prediction case. DYTRAP has been applied to all 2009 tropical cyclone track prediction. The results outperforms those of all models as well as all the official forecasts of the typhoon centers. In order to prove the real usefulness of DYTRAP, it is necessary to apply the DYTRAP system to the real time prediction because the forecast in typhoon centers usually uses 6-hour or 12-hour-old model guidances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.409-411
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• 2014

There have been various advanced research on how changes of analysts' profit forecasts affect stock prices. Also, consensus, which is usually drawn by the arithmetic mean of profit forecasts, has been widely harnessed among investors in stock market. Recently, it is emphasized to reflect the internal factors of individual forecasts to raise the accuracy of consensus. Based on national and international research, this study proposes a new methodology in consensus by applying statistically meaningful factors in computation.

• Journal of Technology Innovation
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• v.9 no.1
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• pp.95-120
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• 2001

One of the systematic attempts for technological forecasting is Delphi Method that externalizes and manipulates unformalized experts opinion in a particular problem or subject. It has, however, a critical shortcoming that it can not reflect the degree of interaction that exists among forecast events or subject. Gordon and Hayward(1969) criticize that when the forecast events are strongly interrelated, a totally unrealistic consensus may result. They proposed a new forecasting method that considers the interaction of events, that is, Cross Impact Analysis (CIA). A number of related models have been developed after them. In this study, we examine a variety of research results related to CIA obtained by literature survey and propose the limitation and future research direction. This analysis would be expected to help us to create a strategic scenario on future technology development at the government and firm level.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.93-124
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• 2003

This paper studies the financial analyst's forecasting activities on the firm's operating performance during the period from 1999 to 2003. In this study, financial analyst's forecasting activities are focused on the sales, operating income and net income and financial analyst's forecasting accuracy, forecasting revising patterns and forecasting activities to the unexpected firm's operating performance are studied. Some empirical findings in this study are as follows. First, standard estimate error on the sales, operating income and net income are all significantly negative value and so financial analyst's forecast on the firm's operating performance are upwardly biased. Second, domestic financial analyst's forecasting activities is relatively more accuracy than foreign financial analyst's forecasting activities. Third, forecasting time is more close to the end of the operating performance announcement day, forecasting activities are more accuracy. Fourth, comparing with individual financial analyst's forecast, consensus forecast is more accuracy. Fifth, in the comparative forecasting activities study according to the prior firm's operating performance, financial analyst's forecasting revision activities are found to be upward or downward. Sixth, financial analysts overreact in the sales forecast and underreact in the operating income and net income forecast. Seventh, in the empirical analysis on the Easterwood-Nutt's test model(1999) which the firm's performance change are divided into the expected performance change and the unexpected performance change, it is found that financial analyst's forecasting activities on the firm's operating performance are systematically optimistic.

• Atmosphere
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• v.26 no.1
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• pp.1-18
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• 2016

Eleven Tropical Cyclone (TC) intensity guidance models in the western North Pacific have been validated over 2008~2014 based on various analysis methods according to the lead time of forecast, year, month, intensity, rapid intensity change, track, and geographical area with an additional focus on TCs that influenced the Korean peninsula. From the evaluation using mean absolute error and correlation coefficients for maximum wind speed forecasts up to 72 h, we found that the Hurricane Weather Research and Forecasting model (HWRF) outperforms all others overall although the Global Forecast System (GFS), the Typhoon Ensemble Prediction System of Japan Meteorological Agency (TEPS), and the Korean version of Weather and Weather Research and Forecasting model (KWRF) also shows a good performance in some lead times of forecast. In particular, HWRF shows the highest performance in predicting the intensity of strong TCs above Category 3, which may be attributed to its highest spatial resolution (~3 km). The Navy Operational Global Prediction Model (NOGAPS) and GFS were the most improved model during 2008~2014. For initial intensity error, two Japanese models, Japan Meteorological Agency Global Spectral Model (JGSM) and TEPS, had the smallest error. In track forecast, the European Centre for Medium-Range Weather Forecasts (ECMWF) and recent GFS model outperformed others. The present results has significant implications for providing basic information for operational forecasters as well as developing ensemble or consensus prediction systems.

• IE interfaces
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• v.17 no.1
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• pp.84-92
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• 2004

We have discussed the importance of collaborative forecasting and the difficulties that can arise during its implementation. We have also proposed the detail process of collaborative forecasting and the system requirement on each step of the process so that the proposed detail process can be easily applied to real life scenario. Lastly, we have talked about a case study of a telecommunication equipment manufacturer that has implemented the proposed collaborative forecasting process that verify the feasibility of the process.

• Journal of Environmental Science International
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• v.20 no.9
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• pp.1095-1104
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• 2011

A survey of professionals employed in marine related fields was conducted on subjects related to marine meteorological forecasts and special reports. The outcome of the survey indicated that the respondents were overall satisfied with the determination of the zones related to marine meteorological forecasts and special reports and with the number of forecast factors, but in regards to the questions about specific adjustment methods, it was found that the respondents perceived a need for adjustment. In addition, although there was a high consensus among the respondents that the criteria for watch and warning in the marine special reports were suitable, they voiced the opinion that it will be necessary to implement changes in the current criteria for watch and warning in order to further improve the compatibility of the criteria. The survey found that there was a high level of utilization for the marine meteorological information provided by the Korea Meteorological Administration(KMA), and that respondents mostly acquired this information via internet and TV. On the other hand, however, the satisfaction level regarding the accuracy of the marine meteorological information was low in comparison to the utilization level. The survey regarding areas for improvement in the forecasts and special reports also indicated that the need for 'improvement in the accuracy of forecasts' was cited most frequently.

• Analyses & Alternatives
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• v.4 no.2
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• pp.71-102
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• 2020

This study analyzes the effect of demographic changes on economic growth. We use the supply-side output identity to forecast the growth potential of the Korean economy. According to the results, even based on optimistic assumptions and prospects, the economic growth rate is likely to fall drastically starting in 2020. Of course, to maintain growth potential, efforts to increase productivity are necessary. However, given the historical experience of developed countries, it is not clear whether the huge trend of demographic change can be offset by efforts to increase productivity. In the so-called '30-50 club' countries, both labor productivity and growth rate tend to fall after reaching the per capita income of $30,000. The degree of decline in the growth rate is closely related to changes in the working age population and the prime-age workforce. The results are similar when tracking the path of changes in total factor productivities of the economy. When a certain level of income is reached, the increase in total factor productivity also tends to slow down. The ripple effects of rapid changes in demographics will indeed be extensive. The negative impact is likely to be concentrated at a time when the working age population, the prime-age workforce, and the total population shrink simultaneously. Above all, it is necessary to use the government's fiscal space to block the possibility of a rapid fall in the growth rate. In addition, it is important to continuously implement various reform tasks that should be promoted, such as improving the education system and strengthening the social safety net.