• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.55-58
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• 2005

This study was Performed to grasp of the problem and improvement in traffic noise environmental impact assessment(EIA). National institute of environmental research(NIER) traffic noise prediction model is in general use in internal EIA. In this study, NIER noise prediction model need to improve in that the predicted results lower than the measured results. The other predict model(KLC KEI) is more accurate. Also the volume and speed of traffic is need to standardize in traffic noise prediction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.587-593
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• 2018

The current road traffic noise prediction programs of Korea, which are widely used, are based upon foreign prediction model. Thus, it is necessary to verify foreign prediction models to find out whether they are suitable for the domestic road traffic environment. In addition, an analysis and an in-depth study on the main factors should be conducted in advance as the influence factors on the occurrence of traffic noise vary for each prediction model. Therefore, this study examined the influence factors and the existing prediction models used to forecast road traffic noise. Also, analyzed their relationship with the factors influencing the noise generated by driving vehicles through multiple regression analysis using a prediction model, taking into consideration of the traffic environment and the road geometric structure. In addition, this study will apply experimental values to the existing road traffic noise prediction model (NIER, RLS-90) and the deducted road traffic noise prediction model. As a result, the order of the absolute value sum of the errors are NIER, RLS-90, model value. Through comparison and verification, developed models are to be analyzed for providing basic research results for future study on road traffic noise prediction modeling.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.11
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• pp.1198-1206
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• 2006

We have carried out highway traffic noise prediction and measurement for 10 sites with representative road shapes and structures. A road traffic noise prediction model(NIER('99)) has been developed for environmental impact assessment in Korea. With the fitted regression analysis, the distribution ratio($R^2$) and Pearson correction coefficient(r) was 92.4% and 0.96 in $1^{st}$ floor, 38.7% and 0.66 in $3^{rd}$ floor, 42% and 0.65 in $5^{th}$ floor, 7.5% and 0.27 in $7^{th}$ floor, 28.4% and 0.53 in 10th floor, 35.6% and 0.60 in $13^{th}$ floor, 52.7% and 0.73 in $15^{th}$ floor, respectively. The measured values of the noise level except the 1st floor did not show a good agreement with the predicted noise level in the NIER('99) formula. Also, the NIER('99) formula demonstrated that the measured values weren't reasonably close to the predicted values, indicating the validity and adequacy of the predicted models with the fitted vs residual analysis in the 95% of confidence interval and 95% of predict interval. Using the equal variation on the basis of the residual vs fitted value, there was the significant difference for variation between $3^{rd}$ floor and $15^{th}$ floor except $1^{st}$ floor. The results suggested that the NIER('99) model obtained by the results according to the apartment floor must be improved and developed on the road traffic noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.751-756
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• 2006

The purpose of this study is to grasp present condition of railroad noise, and forecast noise and presented basis data that ready noise reduction countermeasure. This study has predicted the level of noise reduction according to barrier by considering the characteristics of the cause of noise. These result drew using 'Prediction Model of NIER' and 'Shall03 of Germany'. This paper found important factors in railroad noise using this results and become forward syudy direction.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.54-62
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• 2008

It is often believed that a more complex water quality model is better able to simulate reality. The more complex a model, however, the more parameters are involved thus increases the cost and uncertainty of modeling processes. The objective of this study was to compare the performance of two steady-state river water quality models, QUAL2E and QUAL-NIER, that have different complexity. QUAL-NIER is recently developed by National Institute of Environmental Research aiming to enhance the simulation capability of QUAL2E for eutrophic rivers. It is a carbon based model that considers different forms, such as dissolved versus particulate and labile versus refractory, of carbon and nutrients, and the contribution of autochthonous loading due to algal metabolism. The models were simultaneously applied to Nakdong River and their performance was evaluated by statistical verification with field data. Both models showed similar performance and satisfactorily replicated the longitudinal variations of BOD, T-N, T-P, Chl.a concentrations along the river. The algal blooms occurred at the stagnant reaches of downstream were also reasonably captured by the models. Although QUAL-NIER somewhat reduced the magnitude of errors, the hypothesis tests revealed no statistical evidence to justify its better performance. The contribution of autochthonous carbon and nutrient load by algal metabolism was insignificant because the hydraulic retention time is relatively short compare to the time scale of kinetic reactions. The results imply that the kinetic processes included in QUAL-NIER are too complex for the nature and scale of the real processes involved, thus needs to be optimized for improving the modeling efficiency.

• Journal of Environmental Impact Assessment
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• v.15 no.2
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• pp.93-100
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• 2006

In general, the verification to prediction formula in a national road and the main street of a town has been used recklessly in Korea. Therefore we investigated the validity of an existing prediction formula (NIER(87, 99), TR-Noise, KLC(2002)) with correction relationship which was based on both the prediction formular from apartment complex in the field and height 1.5m from the surface level. On the results of measuring the noise level form an isolated distance, the noise level showed that it was 4.5~5.5dB(A) by reason of becoming 2 folder far from a source. From the distribution of noise level measured by the apartment floors, the measurement point (1st floor) was 58.7~71.4dB(A) at its lowest level and the middle floors (3, 5, 7 and 10) were the highest distribution of noise level. From the analysis results on the application validity to an existing prediction formular (NIER(87, 99), TR-Noise, KLC(2002)) in the height 1.5m, the correction coefficients were 0.95~0.96 and the measured values were reasonably close to the predicted values, indicating the validity and adequacy of the predicted models. KLC(2002) model was found accurate within 3dB(A) with 36 data out of the total 42 data, showing the most accuracy among the predict models. However, the developed models have to improve the accuracy with a various of factors.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.1-4
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• 2008

Prediction models currently being used for road traffic noise in apartment are equation of NIER, HW-NOISE of Korea Expressway Corporation, FHWA of United States, CRTN of United Kingdom, NMPB of France, ASJ RTN-Model 2003 of Japan and ISO 9613-1, 2 as a international standard. ISO 9613 species an engineering method for calculating the attenuation of sound during propagation outdoors in order to predict the levels of environmental noise at a distance from a variety of sources. This study, prior to investigation of every prediction methods listed above, aims to examine the model internationally standardized and to establish a reference for the prediction of road traffic noise in apartment.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.1
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• pp.67-73
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• 2006

10 sites in building development areas were selected and the noise level were measured by the apartment floors of apartment complex. With the fitted regression analysis, the distribution ratio($R^2$) and correction coefficient(r) was 25%(0.5) in the NIER('87) and 7.5%(0.274) in the NIER('99), respectively. The measured values of the noise level on the seventh floor of complex did not show a good agreement with the predicted noise level in the NIER('87, '99) formula. However, the developed formula demonstrated that the measured values were reasonably close to the predicted values, indicating the validity and adequacy of the predicted models with the fitted vs residual analysis in the 95% of confidence interval and 95% of predict interval. The results suggested that application of this development model obtained by the results according to the apartment floor can be improved in road traffic noise.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.83-92
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• 2015

Concerning the national health, it is important to develop an accurate prediction method of atmospheric particulate matter (PM) because being exposed to such fine dust can trigger not only respiratory diseases as well as dermatoses, ophthalmopathies and cardiovascular diseases. The National Institute of Environmental Research (NIER) employs a decision tree to predict bad weather days with a high PM concentration. However, the decision tree method (even with the inherent unstableness) cannot be a suitable model to predict bad weather days which represent only 4% of the entire data. In this paper, while presenting the inaccuracy and inappropriateness of the method used by the NIER, we present the utility of a new prediction model which adopts boosting with quantile loss functions. We evaluate the performance of the new method over various ${\tau}$-value's and justify the proposed method through comparison.

• Korean Journal of Environmental Agriculture
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• v.11 no.1
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• pp.20-25
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• 1992

To understand the fundamental features of reservoir environment and its future aspects, a simple predictive model for water quality was attempted with the aid of data easily obtained, Based on the data from 12 reservoirs in Korea, application of the simple predictive model was successfully made by means of statistical methods and simple physical submodels. Significant information on th effects of retention time on primary production in a reservoir, longitudinal change in water quality affected by certain non-dimensional parameters were also obtained. The chlorophyll-a concentration can be predicted by the equation as ; chlorophyll-a=($395{\time}limiting$ nutrient concentration) - 1.090.