• 제목/요약/키워드: integrated index

검색결과 748건 처리시간 0.029초

날씨효과를 고려한 전력계통의 상정사고 순위 결정 (A Determining Contingency Ranking Using the Weather Effects of the Power System)

  • 김경영;이승혁;김진오;김태균;전동훈;차승태
    • 대한전기학회논문지:전력기술부문A
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    • 제53권9호
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    • pp.487-493
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    • 2004
  • The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RTS. The system performance index for power flow presents the power system stability. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into the case of normal and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking required for security under the deregulated electricity market.

MNDWI와 NDVI의 통합을 통한 내륙습지의 육화현상 추적: 우포늪을 사례로 (Monitoring the Desiccation of Inland Wetland by Combining MNDWI and NDVI: A Case Study of Upo Wetland in South Korea)

  • 황영석;엄정섭
    • Spatial Information Research
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    • 제23권6호
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    • pp.31-41
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    • 2015
  • 본 연구는 육화 추세를 추적하는 과정에서 MNDWI (Modified Normalized Difference Water Index)와 NDVI(Normalized Difference Vegetation Index)를 통합한 접근의 실용성을 평가하는 것을 목적으로 한다. 사례 연구지역인 우포늪에 대해 MNDWI는 수분 지수에 민감하여, 수문 객체는 더욱 강조하고 습윤 토양의 변화를 추적하는 등 수문 객체 외의 요소들은 더욱 강하게 배제하는 근거를 제시하였다. NDVI는 식생의 수령, 식생밀도에 대한 정보를 제시하고, 수분객체와 다른 토지 피복 유형(식생, 건물, 도로 등)을 가시적으로 추적하였다. NDVI와 MNDWI의 통합접근을 통해 산출되는 정량적이고 거시적인 정보는 NDVI와 MNDWI의 변화가 육화에 대한 정량적인 근거로 활용될 수 있다는 의미있는 결과를 보여준다. 본 연구는 향후 내륙습지의 육화에 대한 장기적 모니터링과 전반적인 육화 대응방안을 도출하는 과정에서 NDVI, MNDWI 통합접근의 근거가 되는 기초자료를 제공하였다.

Si3N4 립-광도파로의 두-수평모드 파워결합과 소산파 기반 집적광학 바이오센서 설계 (Design of Integrated-Optic Biosensor Based on the Evanescent-Field and Two-Horizontal Mode Power Coupling of Si3N4 Rib-Optical Waveguide)

  • 정홍식
    • 센서학회지
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    • 제29권3호
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    • pp.172-179
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    • 2020
  • We studied an integrated-optic biosensor configuration that operates at a wavelength of 0.63 ㎛ based on the evanescent-wave and two horizontal mode power coupling of Si3N4 rib-optical waveguides formed on a Si/SiO2/Si3N4/SiO2 multilayer thin films. The sensor consists of a single-mode input waveguide, followed by a two-mode section which acts as the sensing region, and a Y-branch output for separating the two output waveguides. The coupling between the two propagating modes in the sensing region produces a periodically repeated optical power exchanges along the propagation. A light power was steered from one output channel to the other due to the change in the cladding layer (bio-material) refractive index, which affected the effective refractive index (phase-shift) of two modes through evanescent-wave. Waveguide analyses based on the rib optical waveguide dimensions were performed using various numerical computational software. Sensitivity values of 12~23 and 65~165 au/RIU, respectively for the width and length of 4 ㎛, and 3841.46 and 26250 ㎛ of the two-mode region corresponding to the refractive index range 1.36~1.43 and 1.398~1.41, respectively, were obtained.

주가지수예측에서의 변환시점을 반영한 이단계 신경망 예측모형 (Two-Stage Forecasting Using Change-Point Detection and Artificial Neural Networks for Stock Price Index)

  • 오경주;김경재;한인구
    • Asia pacific journal of information systems
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    • 제11권4호
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    • pp.99-111
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    • 2001
  • The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

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Happel Cell 모델을 이용한 막오염 지수 예측 (Prediction of Membrane Fouling Index by Using Happel Cell Model)

  • 박찬혁;김하나;홍승관
    • 상하수도학회지
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    • 제19권5호
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    • pp.632-638
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    • 2005
  • Membrane fouling index such as Silt Density Index (SDI) and Modified Fouling Index (MFI) is an important parameter in design of the integrated RO/NF membrane processes for drinking water treatment. In this study, the effect of particle, membrane and feed water characteristics on membrane fouling index were investigated systematically. Higher fouling index values were observed when filtering suspensions with smaller particle size and higher feed particle concentration. Larger membrane resistance due to smaller pore size resulted in an increased membrane fouling index. The variations of feed water hardness and TDS concentrations did not show any impact on fouling index, suggesting that there were no significant colloidal interactions among particles and thus the porosity of particle cake layer accumulated on the membrane surface could be assumed to be 0.36 according to random packing density. Based on the experimental observations, fundamental membrane fouling index model was developed using Happel Cell. The effect of primary model parameters including particle size ($a_p$), particle concentration ($C_o$), membrane resistance ($R_m$), were accurately assessed without any fitting parameters, and the prediction of membrane fouling index such as MFI exhibited very good agreement with the experimental results.

지속가능한 발전을 위한 통합적인 도시 평가 (An Integrated Assessment of Urban for Sustainable Development)

  • 이우성;정성관;박경훈;유주한;김경태
    • 환경영향평가
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    • 제16권6호
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    • pp.447-465
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    • 2007
  • The purpose of this study is to assess the sustainability in 45 cities of all over Gyeongnam and Gyeongbuk using weights and assessment system developed in leading research. The materials of assessment used statistical data and spatial data were standardized for the systematic result. The assessment score was established using the normal distribution from 25 to 125 for removal of the very smallest and maximum value. According to the results, Tongyeong was assessed the highest by 82.5 score in environmental sustainability index. In economical sustainability index, Pohang, Gumi, Changwon, Yangsan were more than 79 score but Busan, Daegu, Andong were less than 70 score. Ulsan, Geoje, Yangsan were assessed higher in society-institutional sustainability index and Jinju, Munkyeong, Changnyeong were showed higher than other cities by more 79 score in quality of life(QOL)'s sustainability index. In case of integrated sustainability index, Jinju that was the highest sustainability in QOL was assessed by first city. However, Ulsan was assessed the lowest city among others. Therefore cities which have high sustainability will prepare a politic investment program for maintaining current conditions. Cities which have low sustainability will grasp closely the environmental characteristics of urban and present the improvement direction through monitoring continuously. Overall, these results can be used as tools to assess the current cities and predict the future one. It is also necessary to establish a systematic urban planning for livable and sustainable city.

딥 러닝을 이용한 부동산가격지수 예측 (Predicting the Real Estate Price Index Using Deep Learning)

  • 배성완;유정석
    • 부동산연구
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    • 제27권3호
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    • pp.71-86
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    • 2017
  • 본 연구의 목적은 딥 러닝 방법을 부동산가격지수 예측에 적용해보고, 기존의 시계열분석 방법과의 비교를 통해 부동산 시장 예측의 새로운 방법으로서 활용가능성을 확인하는 것이다. 딥 러닝(deep learning)방법인 DNN(Deep Neural Networks)모형 및 LSTM(Long Shot Term Memory networks)모형과 시계열분석 방법인 ARIMA(autoregressive integrated moving average)모형을 이용하여 여러 가지 부동산가격지수에 대한 예측을 시도하였다. 연구결과 첫째, 딥 러닝 방법의 예측력이 시계열분석 방법보다 우수한 것으로 나타났다. 둘째, 딥 러닝 방법 중에서는 DNN모형의 예측력이 LSTM모형의 예측력보다 우수하나 그 정도는 미미한 수준인 것으로 나타났다. 셋째, 딥 러닝 방법과 ARIMA모형은 부동산 가격지수(real estate price index) 중 아파트 실거래가격지수(housing sales price index)에 대한 예측력이 가장 부족한 것으로 나타났다. 향후 딥 러닝 방법을 활용함으로써 부동산 시장에 대한 예측의 정확성을 제고할 수 있을 것으로 기대된다.

AHP를 이용한 지역브랜드의 경쟁력 분석 (An Analysis of the Value of Regional Brand Index by Using AHP)

  • 김관수;오상훈;안동환
    • 농촌계획
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    • 제19권4호
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    • pp.95-104
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    • 2013
  • This study developed three indices for evaluating regional brand value, i.e. awareness index, experience index, and attractiveness index. We used an AHP approach to estimate these indices for 151 rural regions (151 administrative jurisdictions in Korea). Our estimation results show that regional brand index varies considerably across regions by the individual characteristics of interviewee. First, the value of regional brand of local jurisdiction is higher than that of more integrated administrative jurisdiction. Second, the brand value of Gangwon and Jeolla region is higher than that of other regions. Third, the interviewees with school children in the age of 40-50 are likely to have higher regional brand value. The estimation results also show a need for different strategies to develop and improve regional brand.

지형 험준도를 고려한 프로파일 기반 지형참조항법과 관성항법의 결합 알고리즘 (Profile-based TRN/INS Integration Algorithm Considering Terrain Roughness)

  • 유영민;이선민;권재현;유명종;박찬국
    • 제어로봇시스템학회논문지
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    • 제19권2호
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    • pp.131-139
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    • 2013
  • In recent years alternative navigation system such as a DBRN (Data-Base Referenced Navigation) system using geophysical information is getting attention in the military navigation systems in advanced countries. Specifically TRN (Terrain Referenced Navigation) algorithm research is important because TRN system is a practical DBRN application in South Korea at present time. This paper presents an integrated navigation algorithm that combines a linear profile-based TRN and INS (Inertial Navigation System). We propose a correlation analysis method between TRN performance and terrain roughness index. Then we propose a conditional position update scheme that utilizes the position output of the conventional linear profile type TRN depending on the terrain roughness index. Performance of the proposed algorithm is verified through Monte Carlo computer simulations using the actual terrain database. The results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.

Kano-SERVQUAL 통합 접근법을 이용한 자동차 서비스 품질에 대한 고객인식 연구 - H사(社)의 자동차 서비스를 중심으로 - (Customer perception of auto service quality using Kano-SERVQUAL integrated approach - Focusing on the auto service of 'H' company -)

  • 김학균;송해근;박영택
    • 품질경영학회지
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    • 제44권4호
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    • pp.965-981
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    • 2016
  • Purpose: This study aims to propose Kano-SERVQUAL integrated approach as an effective tool for evaluating auto service quality attributes to enhance the use of SERVQUAL. Methods: The Kano-SERVQUAL survey was conducted to evaluate customer perception for 28 auto service quality attributes which were obtained from auto service expert in 'H' company. The correlation analysis of SI(Satisfaction Index), DI(Dissatisfaction Index) and expectation values are conducted in this study. Results: The 28 auto service quality attributes are classified into attractive attributes and one-dimensional attributes. The results of this study show that the correlations between the customers' expectation values and DI is strongly positive correlation with 1% significance level, expectation values and SI is negative correlation with 10% significance level. Conclusion: The results show that the purposed Kano-SERVQUAL integrated approach provides a deeper understanding of service quality attributes in that it distinguishes the customers' expectation values between highly expected attributes(e.g. must-be attribute) and less expected attributes(e.g. attractive attribute).