• 환경영향평가
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• 제21권5호
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• pp.767-779
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• 2012

In case of executing surveys in marine ecosystems, the most important things are scientific selection measures of survey stations that can represent various ecosystems characteristics in subjected areas. The situations show a lot of differences that understand characteristics of marine ecosystems in targeted areas according to selection methods and positions in survey stations. Investigation ranges and station numbers in marine ecosystems are classified according to project characteristics and scales. But, currently a clear divisions or objective standards are not. Therefore, this study tried to provide selection measures of survey station in scientific and objective marine ecosystems through precise analysis among environmental impact statements of coastal development projects until now. In this study, impact scopes of marine ecosystems correspond to physical impact predictions by undertaking projects. Impact ranges were divided into three(physical impact ranges) coastal waters. In case of proposing numbers of survey stations according to this survey ranges, numbers of investigation stations due to minimum survey scopes in targeted projects applied 20~30% of all numbers in survey stations. Number of survey stations due to average investigation scopes within physical impact ranges applied 60~70% of all numbers in investigation stations. Numbers of survey stations due to maximum survey ranges within physical impact scopes applied 10~20% of all numbers in survey stations. So, improvement measures were deducted. Finally, according to prediction ranges in impact of various coastal development projects, several kinds of conclusions are suggested. And, it is thought to be able to use as fundamental database to select investigation stations in marine organisms through this study.

• 한국해양공학회지
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• 제28권3호
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• pp.245-253
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• 2014

This research analyzed the current situation and problems with an environmental impact assessment to provide a rational ocean physics assessment technique for power plant thermal effluent. This research also tried to create an improvement plan for heated effluent diffusion impact assessment by examining the reporting regulations for environmental impact assessment, national and international evaluation guidelines, etc. In the case of evaluating the oceanographic impact of heated effluent discharged from power plants, a pre-investigation is necessary before a full-scale presentence investigation, to accurately predict and minimize power plant construction effects on the surrounding environments. Before this presentence investigation, moreover, an integrated presentence plan, which agrees with the business plan, effect prediction, and post-investigation, needs to be established. A sufficient summit investigation must be made, which considers climate changes, and new and additional power plant construction. For accurate long-term oceanic environmental change prediction, the credibility of effect prediction must be elevated by presenting an evaluation method that is categorized by numerical organization models, verification methods, result presentation, and other things. Furthermore, unproductive conflicts between the people involved in heated effluent evaluation should be reduced by these improvement plans.

• IEIE Transactions on Smart Processing and Computing
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• 제5권6호
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.294-298
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• 2015

In the United States, the completion of Construction Work Zone (CWZ) impact assessments for all federally-funded highway infrastructure improvement projects is mandated, yet it is regarded as a daunting task for state transportation agencies, due to a lack of standardized analytical methods for developing sounder Transportation Management Plans (TMPs). To circumvent these issues, this study aims to create a spatiotemporal modeling framework, dubbed "SWAT" (Spatiotemporal Work zone Assessment for TMPs). This study drew a total of 43,795 traffic sensor reading data collected from heavily trafficked highways in U.S. metropolitan areas. A multilevel-cluster-driven analysis characterized traffic patterns, while being verified using a measurement system analysis. An artificial neural networks model was created to predict potential 24/7 traffic demand automatically, and its predictive power was statistically validated. It is proposed that the predicted traffic patterns will be then incorporated into a what-if scenario analysis that evaluates the impact of numerous alternative construction plans. This study will yield a breakthrough in automating CWZ impact assessments with the first view of a systematic estimation method.

• 한국수자원학회논문집
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• 제55권spc1호
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• pp.1295-1303
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• 2022

안정적인 수도 공급을 위한 상수도관망의 역할이 더욱 주목받음에 따라 비정상 상황에 대한 신속한 탐지와 적절한 대처 역시 중요시되고 있다. 장치에 의존한 탐지기법 등 기존의 방법론에는 한계가 존재하므로 데이터를 이용한 모델 기반의 방법이 개발되었다. 하지만 상수도관망 내 측정 데이터는 불확실성을 가져 실제 사용량과 다르다. 따라서 본 연구에서는 기계학습 방법의 하나인 인공신경망 모델을 이용하여 상수도관망 압력값을 예측함에 있어 데이터 불확실성의 영향을 조사한다. 정규분포를 따르는 임의의 값을 고려하여 데이터에 측정치 오류를 형성하고 측정치 오류 여부 및 종류에 따라 총 9가지 데이터를 인공신경망 모델을 통해 예측해 경향성을 비교한다. 분석을 통해 데이터 불확실성이 증가할수록 모델 성능이 감소하며, 출력데이터의 측정치 오류가 모델 성능에 미치는 정도가 더 큼을 확인하였다. 특히 입력데이터와 출력데이터의 측정 오차 크기가 동일한 경우 예측 정확도는 각각 72.25%, 38.61%로 큰 차이를 보였다. 따라서 ANN 모델 예측 성능 향상을 위해서는 입력 데이터보다 출력데이터인 주절점의 측정 오류 크기를 줄이는 것이 중요하다.

• 대한교통학회지
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• 제5권1호
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• pp.59-74
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• 1987

A prediction is an indispensable element to research of Social Science, especially in Regional planning, City planning, and Transportation planning. Since 1930s, varieties of prediction methods have been developed. In the 1980s, numerical models have been used by high-developed computers. even though the numerical models can be figured mathematically, it could not be applied practically due to it's expertness and complicateness. And even professional planners often can not use their ideas which are valuable experiences in prediction process, because they are not knowledgable for numerical models. The YSIM developed by author, is available as follows. i)Numerical modeling of professional experiences ii)Providing a foundation of large-scale model iii) Understanding of research object structure The YSIM make use of matrix to identify the system structure which is similar to the Cross Impact Method. To evaluated the YSIM availabilities, it is compared with the early developed methodologies such as KSIM, QSIM, and SPIN. As the result, it was confirmed that YSIM was more accurate in the prediction. The algorithms in YSIM is programmed for use of PCs.

• 환경영향평가
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• 제4권1호
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• pp.59-64
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• 1995

Environmental Impact Assesment(EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, mitigation measure, alternative assessment, and post management. Remote sensing introduced lately begins to be applied ecosystem and land use in inventory survey and assessment of EIA. This study explains on land use classification, buffering analysis of residential area, and overlaying analysis of odor predictive data with residential area for application to EIA with remote sensing data. Residential area extracted from land use classification of remote sensing provides effectively buffering analysis of residential area in selection of landfill site with GIS. It could assess also residential effect to an offensive odor by overlaying analysis. Application methods in EIA should be enlarged to assess effectively.

• 한국음향학회지
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• 제2권1호
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• pp.48-58
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• 1983

The transient sound radiation from the impact between a steel ball and a thick plate is analyzed theoretically and compared with experiment results. The derivation process itself is difficult to analyze sound radiation characteristics theoretically for a thick plate with some resonances but may be investigated from measured data. During mechanical impacts, arbitrary driving point importance for an elastic system enables to predict by using mechanical importance method. In order to obtain approximate solution for an impact model testing, the surface Helmholtz integral formulation based on the integral expression for pressure in the field in terms of surface pressure and normal velocity is used as a basis. A simple expression is developed for an impulsive response function, which is time dependent velocity potential and pressure for an impact may then be computed by a convolution of exciting force. In estimating of elastic-acoustical correlation problems, mechanical inertance, overall transfer function and radiation resistance obtained by signal processing techniques are used. The usefulness is confirmed by applying these methods prediction of arbitray driving pint inertance, radiated sound pressure and exciting force.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1994년도 가을 학술발표회 논문집
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• pp.175-182
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• 1994

As for the safety evaluation of existing large-scale structures, methods for estimation of the structural and dynamic properties are studied. Sequential prediction error method in time domain and improved FRF estimator in frequency domain are comparatively studied. For this purpose, impact tests of 2 bay 3 floor steel frame structure are performed. Results from both methods are found to be consistent to each others, however those from the finite-element analysis are slightly different from experimental results.

• 농촌계획
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• 제25권2호
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• pp.99-117
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• 2019

Environmental impact assessment (EIA), which predicts, evaluates, and manages the influences on natural landscape, plays a role of monitoring natural resources for systematic management of natural landscape. However, the function of verification and correction of the system is still insufficient and feed-back, one of the most important features of EIA follow-up, has not been introduced in Korea's EIA system yet. As a procedure, it is required to check if the opinions of the evaluators are properly reflected to the outcomes of the project through a reviewing process after assessing environmental impacts of a development project. In reality, despite the awareness about the importance of follow-up inspection of the conformity with, the system mainly focuses on the agreement during the planning stage of the development project and fails to continuously manage after its completion. There have been various preceding studies related to prediction, evaluation, and management of environmental impacts on natural landscape for better management. They primarily dealt with the problems in the EIA process and suggested improvement measures, including directions for institutional development, step-by-step goals, and operation methods, to address the problems which arise in the EIA follow-up process. However, suggested measures are not actively applied with the focus only put on institutional operation, there are virtually no standardized methods to predict and assess landscape changes due to the development project and to manage landscape after the project. Against this backdrop, this study aims to explore the existing methods to analyze the impacts natural landscape and to establish a system where landscape management is continued after the development project. To this end, we will suggest reducing methods according to the predicted changes in landscape for post-project management of natural landscape. Characteristics of reduction methods by project type were examined through reviewing the guide to natural landscape rating and the importance of development project impacts on natural landscape by type of reduction was evaluated through questionnaire for experts. Evaluated types of reduction are classified and presented by characteristics of each development project and content of reduction type.