• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.280-286
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• 2005

본 논문은 이분형 목적변수를 가지는 데이터에서, 의사결정나무나 신경망과 같은 지도 학습(Supervised Learning)의 훈련을 통한 각종 예측 및 분류 정확도를 향상시키기 위해서 오차 패턴을 이용한 새로운 Hybrid 데이터 마이닝 기법을 제안한다. 오차 패턴을 이용한 Hybrid 기법이란 데이터 마이닝의 서로 다른 기법을 각 데이터에 적용한 다음 기법간의 불일치되는 부분만을 다시 패턴화 하여, 이를 최종 모형에 적용하여, 기존에 1개의 방법만을 사용하였을 경우보다, 더욱 좋은 정확도를 가질 수 있도록 하는 방법이다. 본 기법의 검증을 위하여, 10개의 실제 검증용 자료를 사용하였으며, 분석 결과 신경망과 의사결정나무 분석과 같은 기존의 방법보다 전체적으로 예측력이 향상됨을 보였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.872-876
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• 2007

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.877-881
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• 2007

Recently, noise map is used widely by synthetic estimation method for noise reduction. For correct manufacture of noise map, selection of suitable noise prediction method is important. This study compares XPS31-133 with CRTN, RLS90 which are widely used by foreign commercial noise maps.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.882-886
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• 2007

People living in the large cities are exposed to high level noise due to road-traffic, railway-traffic and aircraft. Nowadays, some researches are ongoing to reduce the noise by using noise map. However it has to be decided which prediction model is the most suitable in Korea. In this study, it has been focused on railway noise prediction models which are employed in a commercial software(Sound Plan) and developed by Korea Railroad Research Institute, and comparative study of the prediction models has been made.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.867-871
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• 2007

Noise map is very efficient tool to evaluate the road traffic noise. However, calculation time and accuracy of noise map heavily depend on the grid size of noise map. In this study, effects of grid size on the prediction results of road traffic noise map have been investigated in detail for urban and rural areas, respectively, and efficient grid size for the noise map has been proposed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.500-504
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• 2008

Residents in an area where both trains and cars pass through are exposed to not only road traffic noise but also railway noise. Nevertheless, the degree of annoyance the caused to the residents is being under evaluated as the noises have been evaluated separately. Therefore, this study aimed at evaluating the integrated noise of road traffic and railway, and proving the accuracy of the evaluation result.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.882-888
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• 2008

The increase in logistics and the emergence of high speed vehicles are aggravating the noise problem, and disturbing large numbers of people. Therefore, growing attention is being paid to the creation and utilization of a noise map in order to grasp and predict the influence of noise, and to establish a policy that effectively reduces noise. However, so far there has been little progress in developing a predictive formula for railway noise, and a noise prediction program suitable for the domestic environment. Therefore, there is a need for a method to apply the overseas prediction formula to domestic railway vehicles. This study evaluated the prediction method, the result of which is similar to that of a real measurement, using a noise map. It also employed a commercial software program, SoundPlan, to predict noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.199-204
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• 2010

Noise map is very efficient tool to evaluate the road traffic noise. However, calculation time and accuracy of noise map heavily depend on the grid size of noise map. In this study, effects of grid size on the prediction results of road traffic noise map have been investigated in detail for urban and rural areas, respectively, and efficient grid size for the noise map has been proposed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.7
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• pp.741-745
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• 2008

Residents in an area where both trains and cars pass through are exposed to not only road traffic noise but also railway noise. Nevertheless, the degree of annoyance the caused to the residents is being under evaluated as the noises have been evaluated separately. Therefore, this study aimed at evaluating the integrated noise of road traffic and railway, and proving the accuracy of the evaluation result.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.2 s.119
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• pp.155-159
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• 2007

Noise map presents new alternatives of noise reduction counter measure and becomes important tool for making environmental policy. Many input factors such as road conditions, number of vehicles, speeds of vehicles are used for noise prediction of the noise map. However, results of noise prediction make difference depending on the values of the input factors. In this study, it researched effect of measurement method for vehicle speeds on the prediction results of the noise map.