• 제목/요약/키워드: Area Prediction.

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새만금 가력도 풍력발전단지에 대한 연간발전량 예측 및 검증 (Prediction and Validation of Annual Energy Production of Garyeok-do Wind Farm in Saemangeum Area)

  • 김형원;송원;백인수
    • 풍력에너지저널
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    • 제9권4호
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    • pp.32-39
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    • 2018
  • In this study, the annual power production of a wind farm according to obstacles and wind data was predicted for the Garyeok-do wind farm in the Saemangeum area. The Saemangeum Garyeok-do wind farm was built in December 2014 by the Korea Rural Community Corporation. Currently, two 1.5 MW wind turbines manufactured by Hyundai Heavy Industries are installed and operated. Automatic weather station data from 2015 to 2017 was used as wind data to predict the annual power production of the wind farm for three consecutive years. For prediction, a commercial computational fluid dynamics tool known to be suitable for wind energy prediction in complex terrain was used. Predictions were made for three cases with or without considering obstacles and wind direction errors. The study found that by considering both obstacles and wind direction errors, prediction errors could be substantially reduced. The prediction errors were within 2.5 % or less for all three years.

Prediction of total sediment load: A case study of Wadi Arbaat in eastern Sudan

  • Aldrees, Ali;Bakheit, Abubakr Taha;Assilzadeh, Hamid
    • Smart Structures and Systems
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    • 제26권6호
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    • pp.781-796
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    • 2020
  • Prediction of total sediment load is essential in an extensive range of problems such as the design of the dead volume of dams, design of stable channels, sediment transport in the rivers, calculation of bridge piers degradation, prediction of sand and gravel mining effects on river-bed equilibrium, determination of the environmental impacts and dredging necessities. This paper is aimed to investigate and predict the total sediment load of the Wadi Arbaat in Eastern Sudan. The study was estimated the sediment load by separate total sediment load into bedload and Suspended Load (SL), independently. Although the sediment records are not sufficient to construct the discharge-sediment yield relationship and Sediment Rating Curve (SRC), the total sediment loads were predicted based on the discharge and Suspended Sediment Concentration (SSC). The turbidity data NTU in water quality has been used for prediction of the SSC in the estimation of suspended Sediment Yield (SY) transport of Wadi Arbaat. The sediment curves can be used for the estimation of the suspended SYs from the watershed area. The amount of information available for Khor Arbaat case study on sediment is poor data. However, the total sediment load is essential for the optimal control of the sediment transport on Khor Arbaat sediment and the protection of the dams on the upper gate area. The results show that the proposed model is found to be considered adequate to predict the total sediment load.

Link Prediction Algorithm for Signed Social Networks Based on Local and Global Tightness

  • Liu, Miao-Miao;Hu, Qing-Cui;Guo, Jing-Feng;Chen, Jing
    • Journal of Information Processing Systems
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    • 제17권2호
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    • pp.213-226
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    • 2021
  • Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.

신설 석유화학 공장의 소음도 예측 (Prediction of the Noise Levels for a Newly-founded Petrochemical Plant)

  • 윤세철;이해경
    • 한국안전학회지
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    • 제11권4호
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    • pp.135-142
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    • 1996
  • Prolonged in-plant personnel exposure to high noise levels results in permant hearing damage. There are no way to correct this hearing damage by treatment or use of hearing aids. Therefore, every employer is responsible for providing a workplace free of such hazards as excessive noise. This study was carried out to evalute and predict a given noise environment based on specific limit as the noise guarantee for a newly-founded petrochemical plant. The maximum total sound level should not exceed 85dBA in the work area, except where the area is defined as a restricted area and 70dBA at the plant boundary. Prediction of the noise levels within the plant area for a newly-founded petrochemical plant was achieved by dividing all plant area into 20m$\times$20m regular grid spaces and noise level inside the area or unit that in-plant personel exposure to high noise levels was estimated computed into 5m$\times$5m regular grid spaces. The noise level at the grid point that was propagated from each of the noise sources(equipments) computed using the methematical formula was defined as follows : $SPL_2$=$SPL_1-20log{\frac{r_2}{r_1}}$(dB) where $SPL_1$ =sound pressure level at distance $r_1$ from the source $SPL_2$=sound pressure level at distance $r_2$ from the source As a result, the equipments exceeded noise limit or irritaring noise levels were identified on the specific grid coordinates. As for equipments in the area that show high noise levels, appropriate counter-measures for noise control (by barriers, enclosure, silencers, or the change of equipments, for example) should be reviewed. Methods for identifying sources of noise applied in this study should be the model for prediction of the noise levels for any newly-founded plant.

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Logistic Regression Type Small Area Estimations Based on Relative Error

  • Hwang, Hee-Jin;Shin, Key-Il
    • 응용통계연구
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    • 제24권3호
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    • pp.445-453
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    • 2011
  • Almost all small area estimations are obtained by minimizing the mean squared error. Recently relative error prediction methods have been developed and adapted to small area estimation. Usually the estimators obtained by using relative error prediction is called a shrinkage estimator. Especially when data set consists of large range values, the shrinkage estimator is known as having good statistical properties and an easy interpretation. In this paper we study the shrinkage estimators based on logistic regression type estimators for small area estimation. Some simulation studies are performed and the Economically Active Population Survey data of 2005 is used for comparison.

Z-map을 이용한 임의의 절삭영역에서의 볼 엔드밀의 절삭력 예측에 관한 연구 (The Study on the Cutting Force Prediction in the Ball-End Milling Process at the Random Cutting Area using Z-map)

  • 김규만
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1996년도 춘계학술대회 논문집
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    • pp.125-129
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    • 1996
  • In this study, a method is proposed for the cutting force prediction of Ball-end milling process using Z-map is proposed. Any types of cutting area generated from previous cutting process can be expressed in z-map data. Cutting edge of a ball-end mill is divided into a set of finite cutting edges and the position of this edge is projected to the cross-section plane normal to the Z-axis. Comparing this projected position with Z-map data of cutting area and determining whether it is in the cutting region, total cutting force can be calculated by means of numerical integration. A series of experiments such as side cutting and upward/downard cutting was performet to verify the simulated cutting force.

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CALPUFF and AERMOD Dispersion Models for Estimating Odor Emissions from Industrial Complex Area Sources

  • Jeong, Sang-Jin
    • Asian Journal of Atmospheric Environment
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    • 제5권1호
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    • pp.1-7
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    • 2011
  • This study assesses the dispersion and emission rates of odor form industrial area source. CALPUFF and AERMOD Gaussian models were used for predicting downwind odor concentration and calculating odor emission rates. The studied region was Seobu industrial complex in Korea. Odor samples were collected five days over a year period in 2006. In-site meteorological data (wind direction and wind speed) were used to predict concentration. The BOOT statistical examination software was used to analyze the data. Comparison between the predicted and field sampled downwind concentration using BOOT analysis indicates that the CALPUFF model prediction is a little better than AERMOD prediction for average downwind odor concentrations. Predicted concentrations of AERMOD model have a little larger scatter than that of CALPUFF model. The results also show odor emission rates of Seobu industrial complex area were an order of 10 smaller than that of beef cattle feed lots.

건물 면적을 이용한 시간별 냉방부하 예측에 관한 연구 (A Study on Prediction of Hourly Cooling Load Using Building Area)

  • 유성연;한규현
    • 설비공학논문집
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    • 제22권11호
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    • pp.798-804
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    • 2010
  • New methodology is proposed to predict the hourly cooling load of the next day using maximum/minimum temperature and building area. The maximum and minimum temperature are obtained from forecasted weather data. The cooling load parameters related to building area are set through a database provided from reference buildings. To validate the performance of the proposed method, the predicted cooling loads in hourly bases are calculated and compared with the measured data. The predicted results show fairly good agreement with the measured data for benchmarking building.

강우앙상블 예측자료의 공간적 특성 및 적용성 평가 (Appraisal of spatial characteristics and applicability of the predicted ensemble rainfall data)

  • 이상협;성연정;김경탁;정영훈
    • 한국수자원학회논문집
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    • 제53권11호
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    • pp.1025-1037
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    • 2020
  • 본 연구는 호우경보에 사용되는 Limited area ENsemble prediction System (LENS) 강우예측자료에 대한 공간적 특성 및 적용성을 평가하였다. LENS는 13개의 강우앙상블 멤버를 가지고 있어 호우경보를 발령하는데 있어 확률적인 방법을 활용할 수 있다. 그러나 LENS의 자료의 접근성은 매우 낮아 강우예측자료의 적용성에 대한 연구가 미흡한 실정이다. 본 연구에서는 행정구역별로 활용되는 호우경보 시스템에 따라 하나의 지점값과 면적평균값을 관측값과 비교하여 평가지수를 산정하였다. 또한, LENS의 발령시간에 따르는 각 앙상블 멤버들의 정확성을 평가하였다. LENS는 멤버별로 과대 혹은 과소 예측의 불확실성을 보여줬다. 면적단위의 예측이 지점단위의 예측보다 더 높은 예측성을 보여주었다. 또한, 다가오는 72시간의 강우를 예측하는 LENS 자료는 수재해의 영향성이 있을 수 있는 강우 사상에 대하여 예측성능이 좋은 것으로 평가되었다. 추후 국지강우앙상블시스템(LENS) 자료는 행정구역 또는 유역면적 단위의 홍수 대비에 기초자료로 활용될 수 있을 것으로 기대된다.

산사태 발생위험 예측을 위한 판정기준표의 작성 -경상북도 지역을 중심으로- (Development of the Score Table for Prediction of Landslide Hazard - A Case Study of Gyeongsangbuk-Do Province -)

  • 정규원;박상준;이창우
    • 한국산림과학회지
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    • 제97권3호
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    • pp.332-339
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    • 2008
  • 경상북도 23개 시․군 산사태 발생지 172개소를 대상지로 선정하여 산사태 발생 특성을 다양한 요인별로 조사 분석하여 산사태 발생 위험 예측을 위한 판정기준표를 작성하였다. 산사태 위험 판정기준표는 수량화 I류를 이용하여 분석하였으며, 산사태 발생량에 영향을 많이 주는 요인은 경사위치, 경사길이, 모암, 방위, 임분경급, 종단명형, 경사도의 순으로 나타났다. 산사태 발생 위험 예측을 위한 산사태 붕괴 위험도 판정기준표를 작성한 결과, 107점 미만 : 안정(IV등급), 107~176점 : 위험도 소(III등급), 177~246점 : 위험도 중(II등급), 247점 이상 : 위험도 대(I등급)로 붕괴 위험도가 구분되었다.