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Finite set model predictive control of permanent magnet synchronous motor current based on super twisting sliding mode observer. [PDF]
PLoS OneRen H, Su C, Long R.
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A sparrow search algorithm-optimized LSTM framework with EMD denoising for rolling element bearing remaining useful life prediction. [PDF]
Sci RepLi Q, Zhang B, Fang X.
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Local Anodic Oxidation of Graphene: The Role of Number of Layers, Load Force, and Substrate. [PDF]
ACS OmegaVymazal J +7 more
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A multivariant exponential shared-load model
IEEE Transactions on Reliability, 1993A shared-load model of the exponential distribution is used to describe the characteristics of dependent redundancies. In the shared-load model, the redundant components equally share the workload. Upon failure of one or more components, the remaining components must carry an increased load.
Lin, Hsin-Hui +2 more
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Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model
IEEE Transactions on Smart Grid, 2016This paper is concerned about real-time modeling and identification of dynamically changing loads in power systems. An exponential dynamic load model was proposed earlier and was well accepted by several investigators who worked on this paper. This paper considers this model and identifies its parameters in real-time based on synchronously sampled ...
Alireza Rouhani, Ali Abur
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IEEE Transactions on Cloud Computing, 2022
More and more enterprises are beginning to use Docker containers to build cloud platforms. Predicting the resource usage of container workload has been an important and challenging problem to improve the performance of cloud computing platform. The existing prediction models either incur large time overhead or have insufficient accuracy.
Yulai Xie +6 more
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More and more enterprises are beginning to use Docker containers to build cloud platforms. Predicting the resource usage of container workload has been an important and challenging problem to improve the performance of cloud computing platform. The existing prediction models either incur large time overhead or have insufficient accuracy.
Yulai Xie +6 more
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IEEE Transactions on Smart Grid, 2014
This paper proposes a model predictive control (MPC)-based voltage/var optimization (VVO) technique considering the integration of distributed generators and load-to-voltage sensitivities. The paper schedules optimal tap positions of on-load tap changer and switch statuses of capacitor banks based on predictive outputs of wind turbines and photovoltaic
Zhaoyu Wang +4 more
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This paper proposes a model predictive control (MPC)-based voltage/var optimization (VVO) technique considering the integration of distributed generators and load-to-voltage sensitivities. The paper schedules optimal tap positions of on-load tap changer and switch statuses of capacitor banks based on predictive outputs of wind turbines and photovoltaic
Zhaoyu Wang +4 more
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Mechanics of Materials, 2012
Abstract The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range ΔK. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub ...
Baptista, C. A. R. P. +3 more
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Abstract The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range ΔK. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub ...
Baptista, C. A. R. P. +3 more
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A Study on Exponential Smoothing Model for Load Forecasting
2012 Asia-Pacific Power and Energy Engineering Conference, 2012Exponential smoothing model is one of the main load forecasting models of power systems, the accuracy of the model depends on smoothing coefficient. In this paper, a study on how to seek the best smoothing coefficient is given. The results show that using the principle of weighting more on near data and weighting less on far data to seek the optimal ...
Peirong Ji +3 more
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