• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.250-251
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• 2021

A subcontract work order is the basis of the construction process and consists of the root and trunk of the construction industry. The construction process through a subcontract work order is an important element of project success, and it is the basic unit of creating profit in the construction industry. Therefore, correct analysis and forecasting of subcontract work orders allow correct estimation of construction cost and profit which is the foundation of corporate decision making. This study has started to provide predictions of subcontractor's bidding-ratio for decision-making. Since the actual project data has been used in this study, the contribution level of the model is highly expected in actual field. The statistical confidential level of adjusted decision coefficient is concluded low because of limited sample numbers. However, its accuracy and confidence level can be increased through increasing sample numbers, considering more variables, and studying of reducing error.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.252-259
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• 2017

Nowadays, the existing manual method for recording actual progress of the construction site has some drawbacks, such as great reliance on the experience of professional engineers, work-intensive, time consuming and error prone. A method integrating computer vision and BIM(Building Information Modeling) is presented for indoor automatic progress monitoring. The developed method can accurately calculate the engineering quantity of target component in the time-lapse images. Firstly, sample images of on-site target are collected for training the classifier. After the construction images are identified by edge detection and classifier, a voting algorithm based on mathematical geometry and vector operation will divide the target contour. Then, according to the camera calibration principle, the image pixel coordinates are conversed into the real world Coordinate and the real coordinates would be corrected with the help of the geometric information in BIM model. Finally, the actual engineering quantity is calculated.

• 한국기계가공학회지
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• 제16권2호
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• pp.22-27
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• 2017

During the water treatment process for household water supply, a reservoir is the last place the water is stored before being supplied to users, and the duration of the water's stay is an important factor that affects its safety. This may cause the concentration of the residual chlorine disinfectant to increase and thus lower the water's quality. The concentration and discharge efficiency of residual chlorine must be verified and managed, because these are key factors that affect the reservoir's performance. Because the actual verification test for analyzing the efficiency of a reservoir and the disinfectant's dilution capacity is difficult, simulations are generally conducted using the computational fluid analysis method. However, the simulation results require validation with experiments. The error and drainage efficiency were analyzed in this study by comparing and analyzing the actual tracer test and simulation so that the actual test for a hexagonal drainage can be replaced by the computational fluid analysis method. Based on the results of the efficiency analysis, the hexagonal reservoir was found to be appropriate, and the simulation's reliability was verified with a tracer test.

• 조명전기설비학회논문지
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• 제20권1호
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• pp.57-64
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• 2006

본 논문에서는 유도전동기의 벡터제어를 위한 ANN 센서리스 제어와 속도제어를 위한 AFLC를 제안하였다. AFLC 설계는 적응 메카니즘을 통해 퍼지 룰 베이스의 수정자를 갱신하여 실행할 수 있고 유도 전동기의 속도 추정을 위한 ANN 센서리스 제어는 BPA를 통해 수행하였다. 유도전동기의 지령속도와 실제속도는 BPA를 통해 그 오차를 줄일 수 있고, 이러한 알고리즘은 다른 전동기 드라이브에 적용이 용이하다. 본 논문에서 제시한 AFLC 및 ANN 제어의 응답특성을 분석하고 그 결과를 제시한다.

• 조명전기설비학회논문지
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• 제25권12호
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• pp.11-20
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• 2011

PSALI is referred to the supplementary lighting for the interior lighting under the daily lighting situation, and pursuant to the pertinent regulations in energy savings design standard and others in recent architecture works, the importance thereof has been increasing gradually coupled with the energy performance index (EPI), energy savings plan and the like as well as expansion of submittal and implementation policies. However, this type of PSALI studies indeed have a number of limitations since it has surrounding environmental conditions in direction, season, region, climate, time, opening rate, window area ratio, actual index, reflection rate of finishing materials and others in the architecture work as well as frequent changes in interior lighting environment for variables in daily light volume flowing into the interior, and others. Therefore, this study has analyzed existing advance research cases to produce the actual-sized model and scaled-down model, and installed the artificial lighting of LED light source possible to reproduce with same capability on both models. As a result of comparison and analysis of the artificial lighting with the key light, it has certain level of error rate from the scaled down lighting device in certain rate and actual model butit was noticeably significant within specific scope.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1478-1481
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• 2005

As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network controller. The back-propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back-propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

• 전력전자학회논문지
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• 제10권3호
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• pp.282-289
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• 2005

본 논문에서는 NFC(Neuro-Fuzzy Controller)와 ANN(Artificial Neural network) 제어기를 이용한 IPMSM의 속도 제어 및 추정을 제시한다. PI 제어기에서 나타나는 문제점을 해결하기 위하여 신경회로망과 퍼지제어를 혼합적용한 NFC를 설계한다. 신경회로망의 고도의 적응제어와 퍼지 제어기의 강인성 제어의 장점들을 접목한다. 다음은 ANN을 이용하여 IPMSM 드라이브의 속도 추정기법을 제시한다. 2층 구조를 가진 신경회로망에 BPA(Back Propagation Algorithm)를 적용하여 IPMSM 드라이브의 속도를 추정한다. 추정속도의 타당성을 입증하기 위하여 시스템을 구성하여 제어특성을 분석한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 B
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• pp.1251-1253
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neuro-fuzzy control(NFC) and estimation of speed using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.171-177
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• 2021

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

• 한국측량학회지
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• 제35권6호
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• pp.545-552
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• 2017

풍성사구는 지표, 바람과 식생간의 상호 작용에 의해 유지${\cdot}$발달되는 대표적인 사구이다. 이러한 사구의 변형을 예측하는 모형을 개발하는 것은 토지 황폐화와 같은 지형 경광의 이해와 관리의 효율성을 높이는데 매우 중요하다. 하지만 기존의 모형에서는 사구의 장기 거동에 대한 연구와 이를 이용한 실제 지형 적용에 관한 연구는 미비한 실정이다. 따라서, 본 연구에서는 식생을 고려한 바람-식생 모형을 실제 지형에 적용하고, 장기 거동을 실제 데이터와 비교하여 바람-식생 모형의 적용성을 분석하였다. 분석을 통해서 바람-식생 모형과 무인항공기 데이터를 이용하는 방법이 경계면을 제외하고 실제 사구지형의 변화와 최대 1m 내외의 오차로 나타나 장기 거동 분석에 효과적인것을 알 수 있었다.