• 제목/요약/키워드: Current prediction

검색결과 1,696건 처리시간 0.024초

Adaptive Prediction Block Filter for Video Coding

  • Yoon, Yeo-Jin;Jung, Seung-Won;Lee, Ha-Hyun;Kim, Hui-Yong;Choi, Jin-Soo;Ko, Sung-Jea
    • ETRI Journal
    • /
    • 제34권1호
    • /
    • pp.106-109
    • /
    • 2012
  • In this letter, we propose a new prediction block filter that can reduce errors between the original and prediction blocks. The proposed filter adaptively adjusts filter coefficients by using the previously reconstructed adjacent blocks and their prediction blocks. Then, the filter is selectively applied to the current prediction block according to the rate-distortion optimization. Moreover, since the same filter coefficients can be derived in the decoder, they are not encoded into the bit-stream. The proposed method achieves a 4.65% bitrate saving on average compared with H.264/AVC.

Response Time Prediction of IoT Service Based on Time Similarity

  • Yang, Huaizhou;Zhang, Li
    • Journal of Computing Science and Engineering
    • /
    • 제11권3호
    • /
    • pp.100-108
    • /
    • 2017
  • In the field of Internet of Things (IoT), smarter embedded devices offer functions via web services. The Quality-of-Service (QoS) prediction is a key measure that guarantees successful IoT service applications. In this study, a collaborative filtering method is presented for predicting response time of IoT service due to time-awareness characteristics of IoT. First, a calculation method of service response time similarity between different users is proposed. Then, to improve prediction accuracy, initial similarity values are adjusted and similar neighbors are selected by a similarity threshold. Finally, via a densified user-item matrix, service response time is predicted by collaborative filtering for current active users. The presented method is validated by experiments on a real web service QoS dataset. Experimental results indicate that better prediction accuracy can be achieved with the presented method.

매입말뚝공법의 지지력 예측식 개선에 관한 연구 (A Study on the Improvement of Bearing Capacity Prediction Equation for Auger-drilled Piling)

  • 최도웅;한병권;서영화;조성한
    • 한국지반공학회:학술대회논문집
    • /
    • 한국지반공학회 2002년도 가을 학술발표회 논문집
    • /
    • pp.382-389
    • /
    • 2002
  • Recently, auger-drilled piling has been widely used in urban area to reduce the air pollution and noise. But this construction method that its basic theory was introduced from Japan may be changed depending on the each piling company and construction field condition. Therefore, the design code and management method for auger-drilled piling is not defined yet. Especially, the lack of research on the bearing capacity of auger-drilled piling leads to the absence of rational bearing capacity prediction equation. This paper presents the optimum design code and economical construction method of the auger-drilled piling by proposing the new bearing capacity prediction equation based on the site specific soil types and construction conditions. In this paper, existing bearing capacity prediction equations and current pile load tests were compared. And the end bearing capacity and skin friction characteristics were also analyzed by comparing the results of CAPWAP. From the results of analysis, a reliable bearing capacity prediction equation considered soil types is proposed.

  • PDF

A study of predicting irradiation-induced transition temperature shift for RPV steels with XGBoost modeling

  • Xu, Chaoliang;Liu, Xiangbing;Wang, Hongke;Li, Yuanfei;Jia, Wenqing;Qian, Wangjie;Quan, Qiwei;Zhang, Huajian;Xue, Fei
    • Nuclear Engineering and Technology
    • /
    • 제53권8호
    • /
    • pp.2610-2615
    • /
    • 2021
  • The prediction of irradiation-induced transition temperature shift for RPV steels is an important method for long term operation of nuclear power plant. Based on the irradiation embrittlement data, an irradiation-induced transition temperature shift prediction model is developed with machine learning method XGBoost. Then the residual, standard deviation and predicted value vs. measured value analysis are conducted to analyze the accuracy of this model. At last, Cu content threshold and saturation values analysis, temperature dependence, Ni/Cu dependence and flux effect are given to verify the reliability. Those results show that the prediction model developed with XGBoost has high accuracy for predicting the irradiation embrittlement trend of RPV steel. The prediction results are consistent with the current understanding of RPV embrittlement mechanism.

신경망을 이용한 영역 행위 예측 (Prediction of Domain Action Using a Neural Network)

  • 이현정;서정연;김학수
    • 인지과학
    • /
    • 제18권2호
    • /
    • pp.179-191
    • /
    • 2007
  • 목적 지향 대화에서 사용자의 의도는 화행과 개념열의 쌍으로 구성된 영역행위로 표현될 수 있다. 사용자 발화에 대한 영역행위 예측은 음성 인식 오류를 보정하는데 유용하며, 시스템 발화에 대한 영역행위 예측은 유연한 응답 생성에 유용하다. 본 논문에서는 신경망을 이용하여 영역행위를 예측하는 모델을 제안한다. 제안 모델은 대화 이력 벡터와 현재 영역행위를 신경망의 입력으로 사용하여 다음 영역행위를 예측한다. 실험 결과, 제안 모델은 화행 예측과 개념열 예측에서 각각 80.02%, 82.09%의 정확률을 보였다.

  • PDF

동적 데이터베이스 기반 태풍 진로 예측 (Dynamic data-base Typhoon Track Prediction (DYTRAP))

  • 이윤제;권혁조;주동찬
    • 대기
    • /
    • 제21권2호
    • /
    • pp.209-220
    • /
    • 2011
  • A new consensus algorithm for the prediction of tropical cyclone track has been developed. Conventional consensus is a simple average of a few fixed models that showed the good performance in track prediction for the past few years. Meanwhile, the consensus in this study is a weighted average of a few models that may change for every individual forecast time. The models are selected as follows. The first step is to find the analogous past tropical cyclone tracks to the current track. The next step is to evaluate the model performances for those past tracks. Finally, we take the weighted average of the selected models. More weight is given to the higher performance model. This new algorithm has been named as DYTRAP (DYnamic data-base Typhoon tRAck Prediction) in the sense that the data base is used to find the analogous past tracks and the effective models for every individual track prediction case. DYTRAP has been applied to all 2009 tropical cyclone track prediction. The results outperforms those of all models as well as all the official forecasts of the typhoon centers. In order to prove the real usefulness of DYTRAP, it is necessary to apply the DYTRAP system to the real time prediction because the forecast in typhoon centers usually uses 6-hour or 12-hour-old model guidances.

교통정보 제공을 위한 교통예측모형의 활용 (Using Traffic Prediction Models for Providing Predictive Traveler Information : Reviews & Prospects)

  • Ran, Bin;Choi, Kee-Choo
    • 대한교통학회지
    • /
    • 제17권1호
    • /
    • pp.141-157
    • /
    • 1999
  • 본 논문은 현재 및 가까운 미래에 있을 교통정보의 제공에 관한 일반적인 가능성으로서 교통현상의 기술이 가능한 교통예측모형의 사용에 대한 총체적인 정리를 함과 함께 바람직한 모형의 제시가 주요 목적이다. 이를 위하여 우선 동적교통배정모형, 통계모형, 모의실험모형, 및 휴리스틱모형이 어떵게 교통정보제공을 위해서 사용될 수 있는지를 각 모형별 제반 특성적 측면에서 검토를 한다. 다음에 이러한 모형의 각종 요구사항이 분석되며, 더 나아가 단기간 교통 상황을 예측하기 위한 각 모형의 능력 및 장단점이 서술적인 관점에서 기술되어진다. 마지막으로, 이러한 각각의 장점을 수용할 수 있을 만한 포괄적인 예측모형의 전형이 그러한 모형을 구축함에 있어서 필요로 하는 데이터의 요구조건과 함께 제시된다.

  • PDF

소규모 만에서 취송류의 신속예측을 위한 convolution 기법의 적용 (Application of the Convolution Method on the Fast Prediction of the Wind-Driven Current in a Samll Bay)

  • 최석원;조규대;윤홍주
    • 한국환경과학회지
    • /
    • 제8권3호
    • /
    • pp.299-307
    • /
    • 1999
  • In order to fast predict the wind-driven current in a small bay, a convolution method in which the wind-driven current can be generated only with the local wind is developed and applied in the idealized bay and the idealized Sachon Bay. The accuracy of the convlution method is assessed through a series of the numerical experiements carried out in the jidealized bay and the idealized Sachon Bay. The optimum response function for the convolution method is obtained by minimizing the root man square (rms) difference between the current given by the numerical model and the current given by the convolution method. The north-south component of the response function shows simultaneous fluctuations in the wind and wind-driven current at marginal region while it shows "sea-saw" fluctuations (in which the wind and wind-driven current have opposite direction) at the central region in the idealized Sachon Bay. The present wind is strong enough to influence on the wind-driven current especially in the idealized Sachon Bay. The spatial average of the rms ratio defined as the ratio of the rms error to the rms speed is 0.05 in the idealized bay and 0.26 in the idealized Sachon Bay. The recover rate of kinetic energy(rrke) is 99% in the idealized bay and 94% in the idealized Sachon Bay. Thus, the predicted wind-driven current by the convolution model is in a good agreement with the computed one by the numerical model in the idealized bay and the idealized Sachon Bay.achon Bay.

  • PDF

신경망을 이용한 세일링 요트 리제너레이션 시스템의 배터리 충전 예측 (Battery charge prediction of sailing yacht regeneration system using neural networks)

  • 이태희;황우성;최명렬
    • 디지털융복합연구
    • /
    • 제18권11호
    • /
    • pp.241-246
    • /
    • 2020
  • 본 논문에서는 해양 전기추진 시스템과 딥러닝 알고리즘을 융합하여 전기추진 리제너레이션 시스템에서 DC/DC 컨버터 출력 전류 예측 및 리제너레이션 수행 시 배터리 충전량을 예측하기 위해 신경망 모델을 제안한다. 제안 된 신경망을 실험하기 위해 PCM의 입력 전압과 전류를 측정하고 시제품 PCM 보드의 출력 결과를 통해 데이터 세트를 구성하였다. 또한 불충분 한 데이터 세트에서 학습 결과를 향상시키기 위해 기존 데이터 세트를 데이터 피팅하여 학습을 진행하였다. 학습 후 신경망 모델의 데이터 예측 결과와 실제 측정 데이터의 차이를 그래프를 통해 확인하였다. 제안한 신경망 모델은 입력 전압과 전류 변화에 따른 배터리 충전량 예측을 효율적으로 보여주었다. 또한, DC/DC 컨버터를 구성하는 아날로그 회로의 특성변화를 신경망을 통하여 예측함으로써, 리제너레이션 시스템의 설계 시, 아날로그 회로의 특성을 고려해야 할 것으로 판단된다.

정전류 스트레스 하에서 게이트 산화막의 항복 특성 예측 (Prediction of gate oxide breakdwon under constant current stresses)

  • 정태식;최우영;이상돈;윤재석;김재영;김봉렬
    • 전자공학회논문지A
    • /
    • 제33A권7호
    • /
    • pp.162-170
    • /
    • 1996
  • A breakdown model of gate oxides under constant current stresses is proposed. This model directly relates the oxide lifetime to the stress current density, and includes statistical nature of oxide breakdown using the concept of "effective oxide thinning". It is shown tha this model can reliably predict the TDDB characteristics for any current stress levels and oxide areas.

  • PDF