• 한국환경과학회지
• /
• 제2권3호
• /
• pp.193-199
• /
• 1993

This study has two objectives. One is developing the runoff model for Hoe-Dong Reservoir basin located at the upstream of Su-Young River in Pusan. To develop the runoff model, basic hydrological parameters - curve number to find effective rainfall, and storage coefficient, etc. - should be estimated. In this study, the effective rainfall was calculated by the SCS method, and the storage coefficient used in the Clark watershed routing was cited from the report of P.E.B. The other is the derivation of transfer function for Hoe-Dong Reservoir basin. The linear, discrete, input-output model which contained six parameters was selected, and the parameters were estimated by the least square method and the correlation function method, respectively. Throughout this study, rainfall and flood discharge data were based on the field observation in 1981.8.22 - 8.23 (typhoon Gladys). It was observed that the Clark watershed routing regenerated the flood hydrograph of typhoon Gladys very well, and this fact showed that the estimated hydrological parameters were relatively correct. Also, the calculated hydrograph by the linear, discrete, input-output model showed good agreement with the regenerated hydrograph at Hoe-Dong Dam site, so this model can be applicable to other small urban areas. Key Words : runoff, effective rainfall, SCS method, clark watershed iou상ng, hydrological parameters, parameter estimation, least square method, correlation function method, input-output model, typhoon gladys.

• 한국수자원학회논문집
• /
• 제49권9호
• /
• pp.789-798
• /
• 2016

최근의 우리나라 수계에서의 하천에서의 조류 대번성은 심각한 사회 환경적 문제가 되고 있다. 이중 독성이 강한 남조류의 발현은 수생태계의 건강성과 안전한 물공급에 위협이 될 수 있다. 영산강 수계의 승촌보와 죽산보 지점의 남조류 세포수와 환경인자간의 인과관계 분석을 위해 선백색화 시계열간의 배타적 상관분석을 수행하였고 이를 기반으로 이들 사이의 입출력 모형을 도출하였다. 입출력 모형의 겨울철 남조류 세포수 반응 특성을 고려하기 위해서 수온의 문턱거동을 도입하였고, 모형의 남조류 세포수에 대한 설명력을 증가시키는 효과를 얻었다. 입출력 모형의 남조류 세포수의 모의능이 완전하진 않으나, 비교적 간단한 구조를 가진 입출력 모형의 구조는 모형 적용의 용이성이 높은 것으로 판단된다.

• Steel and Composite Structures
• /
• 제44권2호
• /
• pp.241-254
• /
• 2022

The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.

• 자원환경지질
• /
• 제47권3호
• /
• pp.237-246
• /
• 2014

본 연구는 산업연관표의 투입산출표와 거시계량경제모형을 연계하여 산업부문에 발생한 충격의 효과가 거시변수에 미치는 효과를 예측할 수 있도록 모형화 하였으며, 모형을 통해 광산품 부문의 수입대체에 따른 경제적 효과를 추정하였다. 구축한 모형의 전반적인 개요는 거시계량경제모형을 구축하고 산업연관표를 통해 도출된 피용자보수를 국민계정상 가처분소득의 대리변수로 이용하여 두 분석틀을 연계하였다. 거시계량경제모형은 한국은행이 작성한 1997년 기준 모형을 근간으로 하여 최근의 한국은행 모형을 통해 수정 및 보완하여 2011년 기준의 연간 거시계량경제모형을 구축하였으며, 산업연관분석과 연계되는 가처분소득과 총취업자수 부분을 수정도입하였다. 산업연관표 부분은 2005년~2011년의 통합대분류 경상표 및 그 계수표를 이용하였다. 구축된 모형을 적용하여 광산품 중간투입 중 1%의 수입대체가 미치는 경제효과를 추정하였는데, 2011년 기준으로 GDP 0.00073% 증가, 경상수지 0.01040% 증가, 실업률 0.00233%p 감소의 효과가 나타났다. 본 연구는 거시변수를 이용하여 지출측면 중심으로 활용되던 거시계량경제모형에 산업연관표를 활용함으로써 산업 수준의 충격과 투입부문을 고려할 수 있도록 하였다는 점에 의의가 있다.

• 생태와환경
• /
• 제43권1호
• /
• pp.161-167
• /
• 2010

In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

• 대한토목학회논문집
• /
• 제14권4호
• /
• pp.859-866
• /
• 1994

대부분의 중소규모 하천 유역에서는 수위 또는 유량 등의 실측자료가 빈약한 상태이기 때문에 홍수시의 유출량을 정확히 추정하고, 홍수피해를 경감시키기 위한 적절한 대책을 세우기가 매우 어려운 실정이다. 본 연구에서는 부산지방에 위치한 온천천 유역을 대상으로 하여 중소 하천 유역에 대한 선형 이산화 입력-출력 모형의 매개변수를 추정하고자 하였으며, 1993년 6월부터 실측한 유출량 자료와 저류함수법에 의해 산정한 유효강우량을 사용하여 선형 이산화 입력-출력 모형의 매개변수를 최소자승법과 상관함수법에 의해 추정하였다. 선형 이산화 입력-출력 모형에 의한 유출 수문곡선은 실측 수문곡선을 잘 재현한 것으로 나타났다. 또한 추정된 매개변수와 강우자료만을 사용하여 모의발생시킨 수문곡선 역시 실측 수문곡선과 잘 일치함을 알 수 있었다.

• 자원ㆍ환경경제연구
• /
• 제14권4호
• /
• pp.839-866
• /
• 2005

본 연구는 우리나라 국가경제에서 중요한 역할을 맡고 있는 원자력부문의 연구개발투자가 국가경제에 미치는 효과를 분석하기 위해, 사례연구로서 한국원자력연구소의 연구개발투자 지출이 국가경제에 미치는 파급효과를 소비, 투자, 수출, 수입, 생산, 부가가치로 구분하여 분석하였다. 분석을 위해 2000년도 산업연관표에 기반을 둔 공급유도형 및 수요유도형 산업연관모형을 구축하였으며 각 모형으로부터 연쇄효과 승수를 도출하여 파급효과를 분석하였다.

• 산업경영시스템학회지
• /
• 제21권46호
• /
• pp.207-219
• /
• 1998

Multiple Objective Programming(MOP) has been suggested for the solution of completed decision problems. Decision analysis in numerous areas, including energy and environmental planning, necessarily requires consideration of multiple conflicting objectives, MOP has been successfully applied to a number of these problems. The objective of this paper is to present a MOP process which are integrated model with the Input-Output(I-O) analysis for energy and environment planning in industrial sectors. In the model, three objectives are observed such as (1) value added (2) total energy consumption and (3) environmental impacts. Special emphasis is placed on the police implications of industrial structures.

• Smart Structures and Systems
• /
• 제24권5호
• /
• pp.617-630
• /
• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2002년도 ITC-CSCC -2
• /
• pp.786-789
• /
• 2002

A recurrent artificial neural network (ANN) model is developed to simulate hydrocarbon recovery process at petroleum-contaminated site. The groundwater extraction rate, vacuum pressure, and saturation hydraulic conductivity are selected as the input variables, while the cumulative hydrocarbon recovery volume is considered as the output variable. The experimental data fer establishing the ANN model are from implementation of a multiphase flow model for dual phase remediation process under different input variable conditions. The complex nonlinear and dynamic relationship between input and output data sets are then identified through the developed ANN model. Reasonable agreements between modeling results and experimental data are observed, which reveals high effectiveness and efficiency of the neural network approach in modeling complex hydrocarbon recovery behavior.