• 환경영향평가
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• 제19권1호
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• pp.15-28
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• 2010

Because deterioration of air quality and urban heat island directly harm health of citizens, Health Impact Assessment (HIA) and Environmental Impact Assessment (EIA) for urban development projects needs to conduct analysis of their impacts objectively. This study aims to review appropriate methods for assessment of air quality used at each stage of urban development and to investigate prediction and assessment methods of urban heat island. In addition, by evaluating impacts of climate change following supposed urban construction performed in the central area of Korea on public health, it examines usefulness of HIA for urban construction. When urban heat island prediction and HIA method suggested in this study are applied to an imaginary city, they predict urban heat island properly and the impacts of climate changes on public health inside the city could be determined clearly by calculating life-climate index and bio-climate index related with thermal environment from the model.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2006년도 하계학술발표대회 논문집
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• pp.295-300
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• 2006

The purpose of this study is to evaluate the impacts of finishing materials' VVOCs and VOCs emission rates on indoor air quality of Apartment. VOCs emission rate of multi-layer finishing is predicted using the effective diffusion coefficient of each materials, and then the prediction is compared with Mock-up test and sample apartment house. From the results, the prediction of multi-layer finishing using the effective diffusion coefficient show good relation with the measured values.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2016년도 추계 학술발표논문집
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• pp.44-48
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• 2016

Extreme temperature impacts on field crop are of key concern and increasingly assessed, however the studies have seldom taken into account the automatic adaptations such as shifts in planting dates, phenological dynamics and cultivars. In this present study, trial data on rice phenology, agro-meteorological hazards and yields during 1981-2009 at 120 national agro-meteorological experiment stations were used. The detailed data provide us a unique opportunity to quantify extreme temperature impacts on rice yield more precisely and in a setting with automatic adaptations.

• 환경영향평가
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• 제9권1호
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• pp.13-24
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• 2000

This paper presents a study of water quality model applications in environmental impact statements which were submitted during recent years in Korea. Most of the applications have reported that the development projects would have significant impacts on the water quality, especially, of streams and rivers. The water quality models, however, were hardly used as an impact prediction tool. Even in the cases where models were used, calibration and verification studies were not performed and thus the predicted results would not be reliable. These poor model applications in environmental impact assessment can be attributable to the fact that there were no available model application guidelines as well as no requirements by the review agency. In addition, the expected waste loads were improperly estimated in most cases, especially in non-point sources, and the predicted parameters were not good enough to understand water quality problems expected from the proposed plans. The effects of mitigation measures were not analyzed in most cases. Again, these can be attributed to no formal guidelines available for impact predictions until now. A brief guideline is described in this paper, including model selection, calibration and verification, impact prediction, and analysis of effects of mitigation measures. The results of this study indicate that the model application should be required to overcome the current improper predictions of environmental impacts and the guidelines should be developed in detail and provided.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.872-875
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• 2009

In a bankruptcy prediction model, the accuracy is one of crucial performance measures due to its significant economic impacts. Ensemble is one of widely used methods for improving the performance of classification and prediction models. Two popular ensemble methods, Bagging and Boosting, have been applied with great success to various machine learning problems using mostly decision trees as base classifiers. In this paper, we analyze the performance of boosted neural networks for improving the performance of traditional neural networks on bankruptcy prediction tasks. Experimental results on Korean firms indicated that the boosted neural networks showed the improved performance over traditional neural networks.

• 대기
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• 제28권2호
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• pp.123-139
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• 2018

The prediction skills of stratospheric sudden warming (SSW) events and its impacts on the tropospheric prediction skills in global seasonal forecasting system version 5 (GloSea5), an operating subseasonal-to-seasonal (S2S) model in Korea Meteorological Administration, are examined. The model successfully predicted SSW events with the maximum lead time of 11.8 and 13.2 days in terms of anomaly correlation coefficient (ACC) and mean squared skill score (MSSS), respectively. The prediction skills are mainly determined by phase error of zonal wave-number 1 with a minor contribution of zonal wavenumber 2 error. It is also found that an enhanced prediction of SSW events tends to increase the tropospheric prediction skills. This result suggests that well-resolved stratospheric processes in GloSea5 can improve S2S prediction in the troposphere.

• ETRI Journal
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• 제45권2호
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• pp.329-337
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• 2023

For safe last-mile autonomous robot delivery services in complex environments, rapid and accurate collision prediction and detection is vital. This study proposes a suitable neural network model that relies on multiple navigation sensors. A light detection and ranging technique is used to measure the relative distances to potential collision obstacles along the robot's path of motion, and an accelerometer is used to detect impacts. The proposed method tightly couples relative distance and acceleration time-series data in a complementary fashion to minimize errors. A long short-term memory, fully connected layer, and SoftMax function are integrated to train and classify the rapidly changing collision countermeasure state during robot motion. Simulation results show that the proposed method effectively performs collision prediction and detection for various obstacles.

• 환경영향평가
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• 제1권1호
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• pp.41-50
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• 1992

To prevent unwanted visual impacts of proposed projects before they are actually built, Visual Impact Assessment(VIA) is conducted in current landscape planning and management process. The application of VIA to actual projects raises some important questions: "What views will the project affect?" "What tools and techniques are effective for predicting and portraying future landscape conditions?" "Who should determine the value of the impacts?" and "How can the impacts be measured?" Types and levels of visual impacts should be decided through analyzing both the existing landscape and the proposed project. Computer-based visual simulations will play a pivotal role as effective prediction and communication tools. With professionals' assistance, the public participation in the VIA process will produce meaningful solutions for planning and managing the future landscape. Also, the use of a proper response format and sensitive assessment criteria in measuring the public's opinion will enrich outcomes of the assessment. Based on the methodological framework, the case study briefly explains an application of VIA to an actual project.

• 환경영향평가
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• 제15권3호
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• pp.165-178
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• 2006

Environmental Impact Assessment (EIA) and Environmental Management Systems (EMS) are perceived by many to be separate environmental tools. EIA serves as a systematic and predictive tool for assessing the potentially significant impacts of developments on the environment. An EMS, on the other hand, is used to consider the key impacts of operational businesses on the environment. The main difference to note is that during the EIA process impacts on developments are predicted. A proposed development has yet to be built and therefore an element of uncertainty is associated with these assessments. With an EMS, the business or organization's processes are already in operation. Even though there is also an element of prediction involved, it is a comparatively easier task to investigate what the environmental impacts of these processes are. However, in contrast with the orientation of EIA to further development actions, EMS involves the review, assessment and incremental improvement of an existing organization's environmental effects. EMS can thus be regarded as a continuation of EIA principles into the operational stage of a policy, plan, program and project. EIA may be carried out without fully supporting necessary informations to EMS.

• 대기
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• 제28권2호
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• pp.153-162
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• 2018

The statistical prediction model for wintertime surface air temperature, that is based on snow cover extent and Arctic sea ice concentration, is updated by considering $El-Ni{\tilde{n}}o$ Southern Oscillation (ENSO) and Quasi-Biennial Oscillation (QBO). These additional factors, representing leading modes of interannual variability in the troposphere and stratosphere, enhance the seasonal prediction over the Northern Hemispheric surface air temperature, even though their impacts are dependent on the predicted month and region. In particular, the prediction of Korean surface air temperature in midwinter is substantially improved. In December, ENSO improved about 10% of prediction skill compared without it. In January, ENSO and QBO jointly helped to enhance prediction skill up to 36%. These results suggest that wintertime surface air temperature in Korea can be better predicted by considering not only high-latitude surface conditions (i.e., Eurasian snow cover extent and Arctic sea ice concentration) but also equatorial sea surface temperature and stratospheric circulation.