• 제목/요약/키워드: Random indices

검색결과 135건 처리시간 0.022초

풍력발전을 포함한 시스템의 발전량 적정성 평가를 위한 비순차 샘플링 방법 (A Random Sampling Method for Generation Adequacy Assessment Including Wind-Power)

  • 김광원
    • 조명전기설비학회논문지
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    • 제25권5호
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    • pp.45-53
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    • 2011
  • This paper presents a novel random sampling method for generation adequacy assessment including wind-power. Although a time sequential sampling has advantages than a random sampling in its assessment results, it takes long assessment time. Therefore, an effective random sampling method for generation adequacy assessment is highly recommended to get specific reliability indices quickly. The proposed method is based on the Monte-Carlo simulation with state sampling and it can be applied to generation adequacy assessment with other intermittent power sources.

Performance-based reliability assessment of RC shear walls using stochastic FE analysis

  • Nosoudi, Arina;Dabbagh, Hooshang;Yazdani, Azad
    • Structural Engineering and Mechanics
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    • 제80권6호
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    • pp.645-655
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    • 2021
  • Performance-based reliability analysis is a practical approach to investigate the seismic performance and stochastic nonlinear response of structures considering a random process. This is significant due to the uncertainties involved in every aspect of the analysis. Therefore, the present study aims to evaluate the performance-based reliability within a stochastic finite element (FE) framework for reinforced concrete (RC) shear walls that are considered as one of the most essential elements of structures. To accomplish this purpose, deterministic FE analyses are conducted for both squat and slender shear walls to validate numerical models through experimental results. The presented numerical analysis is performed by using the ABAQUS FE program. Afterwards, a random-effects investigation is carried out to consider the influence of different random variables on the lateral load-top displacement behavior of RC members. Using these results and through utilizing the Monte-Carlo simulation method, stochastic nonlinear analyses are also performed to generate random FE models based on input parameters and their probabilistic distributions. In order to evaluate the reliability of RC walls, failure probabilities and corresponding reliability indices are calculated at life safety and collapse prevention levels of performance as suggested by FEMA 356. Moreover, based on reliability indices, capacity reduction factors are determined subjected to shear for all specimens that are designed according to the ACI 318 Building Code. Obtained results show that the lateral load and the compressive strength of concrete have the highest effects on load-displacement responses compared to those of other random variables. It is also found that the probability of shear failure for the squat wall is slightly lower than that for slender walls. This implies that 𝛽 values are higher in a non-ductile mode of failure. Besides, the reliability of both squat and slender shear walls does not change significantly in the case of varying capacity reduction factors.

The evaluation of Spectral Vegetation Indices for Classification of Nutritional Deficiency in Rice Using Machine Learning Method

  • Jaekyeong Baek;Wan-Gyu Sang;Dongwon Kwon;Sungyul Chanag;Hyeojin Bak;Ho-young Ban;Jung-Il Cho
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2022년도 추계학술대회
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    • pp.88-88
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    • 2022
  • Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

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ON THE WEAK LAWS WITH RANDOM INDICES FOR PARTIAL SUMS FOR ARRAYS OF RANDOM ELEMENTS IN MARTINGALE TYPE p BANACH SPACES

  • Sung, Soo-Hak;Hu, Tien-Chung;Volodin, Andrei I.
    • 대한수학회보
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    • 제43권3호
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    • pp.543-549
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    • 2006
  • Sung et al. [13] obtained a WLLN (weak law of large numbers) for the array $\{X_{{ni},\;u_n{\leq}i{\leq}v_n,\;n{\leq}1\}$ of random variables under a Cesaro type condition, where $\{u_n{\geq}-{\infty},\;n{\geq}1\}$ and $\{v_n{\leq}+{\infty},\;n{\geq}1\}$ large two sequences of integers. In this paper, we extend the result of Sung et al. [13] to a martingale type p Banach space.

단순 확산과정들에 대한 확률효과 모형 (Random effect models for simple diffusions)

  • 이은경;이인석;이윤동
    • 응용통계연구
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    • 제31권6호
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    • pp.801-810
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    • 2018
  • 확산은 금융이나 물리적 현상의 모형화에 이용되는 확률과정이다. 반복적으로 관측된 확산과정에 대하여 통계적인 모형을 구축할 때, 확률효과를 고려할 필요가 있다. 이 연구에서는 Ornstein-Uhlenbeck 확산모형과 geometric Brownian motion 확산모형에 대하여 확률효과를 도입한다. 모형모수에 대한 최도우도추정법을 적용하기 위하여, 확률효과에 대한 적절한 분포를 가정하여 닫힌 형태로 우도함수를 얻는 방법을 탐색하였다. 1991년부터 2017년까지 27년간 일일 단위로 기록된 다우존스 산업지수에 대하여 확률효과 모형을 적용하였다.

Reliability-based assessment of American and European specifications for square CFT stub columns

  • Lu, Zhao-Hui;Zhao, Yan-Gang;Yu, Zhi-Wu;Chen, Cheng
    • Steel and Composite Structures
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    • 제19권4호
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    • pp.811-827
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    • 2015
  • This paper presents a probabilistic investigation of American and European specifications (i.e., AISC and Eurocode 4) for square concrete-filled steel tubular (CFT) stub columns. The study is based on experimental results of 100 axially loaded square CFT stub columns from the literature. By comparing experimental results for ultimate loads with code-predicted column resistances, the uncertainty of resistance models is analyzed and it is found that the modeling uncertainty parameter can be described using random variables of lognormal distribution. Reliability analyses were then performed with/without considering the modeling uncertainty parameter and the safety level of the specifications is evaluated in terms of sufficient and uniform reliability criteria. Results show that: (1) The AISC design code provided slightly conservative results of square CFT stub columns with reliability indices larger than 3.25 and the uniformness of reliability indices is no better because of the quality of the resistance model; (2) The uniformness of reliability indices for the Eurocode 4 was better than that of AISC, but the reliability indices of columns designed following the Eurocode 4 were found to be quite below the target reliability level of Eurocode 4.

Terra MODIS 위성영상과의 비교를 통한 COMS GOCI 위성영상의 식생지수 적용성 평가 (Applicability of Vegetation Indices from Terra MODIS and COMS GOCI Imageries)

  • 박진기;김봉섭;오시영;박종화
    • 한국농공학회논문집
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    • 제55권6호
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    • pp.47-55
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    • 2013
  • The objective of this study is to evaluate the applicability of Communication, Ocean, and Meteorological Satellite (COMS) Geostationary Ocean Color Imager (GOCI) vegetation indices on a quantitative analysis. For evaluation, the vegetation indices such as RVI, NDVI and SAVI were extracted by using COMS GOCI and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) imageries. The 4,000 points using simple random sampling (SRS) method were randomly extracted from land areas except ocean to compare the vegetation indices from two images. The results of linear regression showed that the regression coefficients of RVI, NDVI, and SAVI between COMS GOCI and Terra MODIS were 0.66~0.82, 0.71~0.83, and 0.71~0.83, respectively. Especially, the regression coefficients of RVI (r=0.85), NDVI (r=0.91) and SAVI (r=0.91) were strongly related from September 2011 to January 2012. Thus, COMS GOCI can be substituted for particular periods and it needs to verify additionally.

Comparison of Frequencies in Order to Estimate of Tree Species Diversity in Caspian Forests of Iran

  • Mirzaei, Mehrdad;Bahnemiry, Atefeh Karimiyan;Abkenar, Kambiz Taheri
    • Journal of Forest and Environmental Science
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    • 제35권1호
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    • pp.1-5
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    • 2019
  • Species diversity is one of the most important indices that used to evaluate the sustainability of forest communities. In the present study, three variables including number of individuals (frequency of species), basal area and volume of tree species were compared to estimate tree species diversity in broadleaves forests of Iran. Based on systematic random design, 30 plots (circle plot, $1000m^2$) was selected. Type of species, number of species, DBH and height of trees were measured. Simpson (1-D), Hill ($N_2$), Shannon-Wiener (H'), Mc Arthur ($N_1$), Smith-Wilson ($E_{var}$) and Margalef ($R_1$) indices used to estimate tree species diversity. Species diversity was calculated in each plot. ANOVA test showed that there was a significant difference between of three variables used for estimation of species diversity. Number of trees variable has more precision than basal area and volume variables to estimate of species diversity. But Duncan test revealed that there were significant difference between of basal area and volume variables with number of trees. Therefore, basal area and volume variables were selected as more suitable variables in order to estimate of biodiversity indices in northern forests of Iran.

SWAT 및 random forest를 이용한 기후변화에 따른 한강유역의 수생태계 건강성 지수 영향 평가 (Assessment of climate change impact on aquatic ecology health indices in Han river basin using SWAT and random forest)

  • 우소영;정충길;김진욱;김성준
    • 한국수자원학회논문집
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    • 제51권10호
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    • pp.863-874
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    • 2018
  • 본 연구에서는 SWAT 모형과 random forest를 이용하여 미래 기후변화에 따른 한강유역($34,148km^2$)의 수생태계 건강성을 평가하였다. 국립환경과학원에서 8년간(2008~2015년) 봄철(4~6월)에 모니터링한 부착돌말류 지수(TDI), 저서형 대형무척추동물지수(BMI), 어류평가지수(FAI)는 0~100점, A~E등급으로 평가되며, 이를 본 연구에서 사용하였다. 수생태 건강성에 영향을 미치는 변수로는 수질(T-N, $NH_4$, $NO_3$, T-P, $PO_4$)과 수온을 선정하였으며, 수질 오염도가 낮은 경우에는 수생태계 건강성 점수가 광범위하게 분포되지만 수질 오염도가 높은 경우 수생태계 건강성 점수가 낮아지는 역상관관계를 확인하였다. 기계학습의 분류 분석 기법 중 하나인 random forest 모델을 이용한 세 개의 수생태 건강성 지수 등급분류 결과 정밀도, 재현율, f1-score 모두 0.81 이상의 예측 정확도를 나타내었다. 기상청의 HadGEM3-RA RCP 4.5와 8.5 시나리오를 적용한 미래 SWAT 수문, 수질 결과 기저유출의 증가로 인해 질소 계열 수질 농도는 기준년도 대비 최대 43.2% 증가하였고, 지표유출 감소로 인해 인 계열수질 오염도는 최대 18.9% 감소하는 것으로 분석되었다. 미래 FAI, BMI의 등급은 개선되는 경향을 보이지만 TDI는 등급이 악화되는 것으로 나타났다. 이를 통해 TDI는 질소 계열 수질에 민감하고 FAI, BMI는 인 계열 수질에 더 민감하다고 판단하였다.

Random Forest Model for Silicon-to-SPICE Gap and FinFET Design Attribute Identification

  • Won, Hyosig;Shimazu, Katsuhiro
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권5호
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    • pp.358-365
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    • 2016
  • We propose a novel application of random forest, a machine learning-based general classification algorithm, to analyze the influence of design attributes on the silicon-to-SPICE (S2S) gap. To improve modeling accuracy, we introduce magnification of learning data as well as randomization for the counting of design attributes to be used for each tree in the forest. From the automatically generated decision trees, we can extract the so-called importance and impact indices, which identify the most significant design attributes determining the S2S gap. We apply the proposed method to actual silicon data, and observe that the identified design attributes show a clear trend in the S2S gap. We finally unveil 10nm key fin-shaped field effect transistor (FinFET) structures that result in a large S2S gap using the measurement data from 10nm test vehicles specialized for model-hardware correlation.