• 제목/요약/키워드: Ensemble Scheme

검색결과 51건 처리시간 0.029초

여름강수량의 단기예측을 위한 Multi-Ensemble GCMs 기반 시공간적 Downscaling 기법 개발 (Development of Multi-Ensemble GCMs Based Spatio-Temporal Downscaling Scheme for Short-term Prediction)

  • 권현한;민영미
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.1142-1146
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    • 2009
  • A rainfall simulation and forecasting technique that can generate daily rainfall sequences conditional on multi-model ensemble GCMs is developed and applied to data in Korea for the major rainy season. The GCM forecasts are provided by APEC climate center. A Weather State Based Downscaling Model (WSDM) is used to map teleconnections from ocean-atmosphere data or key state variables from numerical integrations of Ocean-Atmosphere General Circulation Models to simulate daily sequences at multiple rain gauges. The method presented is general and is applied to the wet season which is JJA(June-July-August) data in Korea. The sequences of weather states identified by the EM algorithm are shown to correspond to dominant synoptic-scale features of rainfall generating mechanisms. Application of the methodology to seasonal rainfall forecasts using empirical teleconnections and GCM derived climate forecast are discussed.

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PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation

  • Kim, Aeyoung;Wang, Changda;Seo, Seung-Hyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권7호
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    • pp.2919-2937
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    • 2020
  • Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.

Asymmetric Semi-Supervised Boosting Scheme for Interactive Image Retrieval

  • Wu, Jun;Lu, Ming-Yu
    • ETRI Journal
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    • 제32권5호
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    • pp.766-773
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    • 2010
  • Support vector machine (SVM) active learning plays a key role in the interactive content-based image retrieval (CBIR) community. However, the regular SVM active learning is challenged by what we call "the small example problem" and "the asymmetric distribution problem." This paper attempts to integrate the merits of semi-supervised learning, ensemble learning, and active learning into the interactive CBIR. Concretely, unlabeled images are exploited to facilitate boosting by helping augment the diversity among base SVM classifiers, and then the learned ensemble model is used to identify the most informative images for active learning. In particular, a bias-weighting mechanism is developed to guide the ensemble model to pay more attention on positive images than negative images. Experiments on 5000 Corel images show that the proposed method yields better retrieval performance by an amount of 0.16 in mean average precision compared to regular SVM active learning, which is more effective than some existing improved variants of SVM active learning.

Multiclass LS-SVM ensemble for large data

  • Hwang, Hyungtae
    • Journal of the Korean Data and Information Science Society
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    • 제26권6호
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    • pp.1557-1563
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    • 2015
  • Multiclass classification is typically performed using the voting scheme method based on combining binary classifications. In this paper we propose multiclass classification method for large data, which can be regarded as the revised one-vs-all method. The multiclass classification is performed by using the hat matrix of least squares support vector machine (LS-SVM) ensemble, which is obtained by aggregating individual LS-SVM trained on each subset of whole large data. The cross validation function is defined to select the optimal values of hyperparameters which affect the performance of multiclass LS-SVM proposed. We obtain the generalized cross validation function to reduce computational burden of cross validation function. Experimental results are then presented which indicate the performance of the proposed method.

다중 기상모델 앙상블을 활용한 다지점 강우시나리오 상세화 기법 개발 (Development of Multisite Spatio-Temporal Downscaling Model for Rainfall Using GCM Multi Model Ensemble)

  • 김태정;김기영;권현한
    • 대한토목학회논문집
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    • 제35권2호
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    • pp.327-340
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    • 2015
  • 기후모형으로 가장 널리 사용되는 GCM의 불확실성 및 시공간적 편의로 인하여 GCM으로부터 생산된 기상정보를 응용수문분야에서 직접적으로 이용하기 위해서는 상세화 과정이 필수적으로 요구된다. 본 연구에서는 선행연구에서 개발된 비정상성 은닉 마코프 모형(Non-stationary Hidden Markov Chain Model, NHMM)을 기반으로 다지점 공간상관성을 고려할 수 있는 Chow-Liu Tree 알고리즘과 결합하여 유역단위 강우시나리오 상세화 기법(CLT-NHMM)으로 확장하였으며, 낙동강 유역에 적용하여 적용성을 평가하였다. 상관행렬(correlation matrix)을 통한 강우네트워크의 공간상관성 평가결과 유역상관성이 우수하게 모의하는 것을 확인하였으며, 강수의 빈도 및 양적 관점에서 효과적인 모의가 가능하였다. 본 연구에서 제시한 CLT-NHMM 모형은 수자원뿐만 아니라 수문자료를 입력 자료로 하는 농업, 보건, 환경 및 에너지 등 다양한 응용기상분야에 핵심 기술로 활용이 전망된다.

장마 강수를 위한 앙상블 통계 예측 모델 개발 (The Development of Ensemble Statistical Prediction Model for Changma Precipitation)

  • 김진용;서경환
    • 대기
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    • 제24권4호
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    • pp.533-540
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    • 2014
  • Statistical forecast models for the prediction of the summertime Changma precipitation have been developed in this study. As effective predictors for the Changma precipitation, the springtime sea surface temperature (SST) anomalies over the North Atlantic (NA1), the North Pacific (NPC) and the tropical Pacific Ocean (CNINO) has been suggested in Lee and Seo (2013). To further improve the performance of the statistical prediction scheme, we select other potential predictors and construct 2 additional statistical models. The selected predictors are the Northern Indian Ocean (NIO) and the Bering Sea (BS) SST anomalies, and the spring Eurasian snow cover anomaly (EUSC). Then, using the total three statistical prediction models, a simple ensemble-mean prediction is performed. The resulting correlation skill score reaches as high as ~0.90 for the last 21 years, which is ~16% increase in the skill compared to the prediction model by Lee and Seo (2013). The EUSC and BS predictors are related to a strengthening of the Okhotsk high, leading to an enhancement of the Changma front. The NIO predictor induces the cyclonic anomalies to the southwest of the Korean peninsula and southeasterly flows toward the peninsula, giving rise to an increase in the Changma precipitation.

법음성학에서의 오디오 신호의 위변조 구간 자동 검출 방법 연구 (An Automatic Method of Detecting Audio Signal Tampering in Forensic Phonetics)

  • 양일호;김경화;김명재;백록선;허희수;유하진
    • 말소리와 음성과학
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    • 제6권2호
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    • pp.21-28
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    • 2014
  • We propose a novel scheme for digital audio authentication of given audio files which are edited by inserting small audio segments from different environmental sources. The purpose of this research is to detect inserted sections from given audio files. We expect that the proposed method will assist human investigators by notifying suspected audio section which considered to be recorded or transmitted on different environments. GMM-UBM and GSV-SVM are applied for modeling the dominant environment of a given audio file. Four kinds of likelihood ratio based scores and SVM score are used to measure the likelihood for a dominant environment model. We also use an ensemble score which is a combination of the aforementioned five kinds of scores. In the experimental results, the proposed method shows the lowest average equal error rate when we use the ensemble score. Even when dominant environments were unknown, the proposed method gives a similar accuracy.

수문기상학적 활용을 위한 레이더 강우자료 생산(II) : 레이더 강우앙상블 (Generation of radar rainfall data for hydrological and meteorological application (II) : radar rainfall ensemble)

  • 김태정;이동률;장상민;권현한
    • 한국수자원학회논문집
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    • 제50권1호
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    • pp.17-28
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    • 2017
  • 최근 국지성 집중호우 및 돌발홍수와 같은 급격한 기상변화로 인한 기상재해의 발생빈도가 증가함에 따라 고해상도의 기상레이더 강우자료를 사용한 수공학 분야의 연구가 활발하게 진행되고 있다. 기상레이더는 넓은 지역에 걸쳐 실시간으로 강우현상 감시가 가능하며 지상우량계로는 파악이 불가능한 미계측유역을 통과하는 강우장의 이동 및 변동성 파악이 가능한 장점이 있지만 대기 중 존재하는 수상체로부터 반사되는 반사도를 사용하여 강우량을 산정하므로 시공간적 오차가 존재한다. 본 연구에서는 이러한 문제점을 해결하기 위하여 다변량 Copula 함수를 활용하여 레이더 강우에 존재하는 시공간적 오차를 규명하고 레이더 강우앙상블 생산기법을 개발하였다. 개발된 모형으로부터 생산된 레이더 강우앙상블은 통계적 효율기준 분석결과 우수한 모형성능을 확인하였으며 추가적으로 극치호우 및 강우시계열 패턴 분석결과 지상강우의 특성을 효과적으로 재현하는 것을 확인하였다.

설계응답스펙트럼에 부합하는 목표 PSD함수의 작성 (Generation of Target PSD Function Compatible with Design Response Spectrum)

  • 이상훈;최동호
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2006년도 학술발표회 논문집
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    • pp.637-644
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    • 2006
  • Acceleration time history used in the seismic analysis of nuclear porter plant structure should envelop a target power spectral density (PSD) function in addition to design response spectrum. Current regulation guide defines the target PSD function only for the U.S. URC RG 1.60 Design Response Spectrum. This paper proposes a technical scheme to obtain the target PSD function compatible with generally defined design response spectrum. The scheme includes the methodology for design-spectrum compatible motion history in order to minimize the variation of the derived target PSD function. The PSD calculation procedure follows simple and practical methods allowed within regulation. Effectiveness of the proposed scheme is identified through an example problem. The design response spectrum In the example is based on U.S. NRC RG 1.60 but amplifies the spectral acceleration amplitudes above 9Hz. The target PSD function with little variation can be constructed with the reduced time history ensemble.

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Application of frequency domain analysis for generation of seismic floor response spectra

  • Ghosh, A.K.
    • Structural Engineering and Mechanics
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    • 제10권1호
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    • pp.17-26
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    • 2000
  • This paper presents a case study with a multi-degree-of-freedom (MDOF) system where the Floor Response Spectra (FRS) have been derived from a large ensemble of ground motion accelerograms. The FRS are evaluated by the frequency response function which is calculated numerically. The advantage of this scheme over a repetitive time-history analysis of the entire structure for each accelerogram of the set has been highlighted. The present procedure permits generation of FRS with a specified probability of exceedence.