Zobrazeno 1 - 10
of 1 518
pro vyhledávání: '"gaussian mixture model (gmm)"'
Autor:
R. Saravanakumar, T. TamilSelvi, Digvijay Pandey, Binay Kumar Pandey, Darshan A. Mahajan, Mesfin Esayas Lelisho
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-29 (2024)
Abstract The traditional methods used in big data, like cluster creation and query-based data extraction, fail to yield accurate results on massive networks. To address such issues, the proposed approach involves using the Hadoop Distributed File Sys
Externí odkaz:
https://doaj.org/article/d078bbed49be4f47b192e3010e8c29b3
Autor:
Deba Datta Mandal, Mourad Bentahar, Abderrahim El Mahi, Alexandre Brouste, Rachid El Guerjouma, Silvio Montresor, François-Baptiste Cartiaux, Jorge Semiao
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract This work presents an acoustic emission (AE) based method, named a series of narrow partial power bands (SN2PB), to monitor the damage mechanisms within reinforced concrete beams during quasi-static bending tests. Unlike conventional time-do
Externí odkaz:
https://doaj.org/article/cbd46b071d754fb7a3124f635581ec80
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
Due to the fluctuating and intermittent nature of wind energy, its prediction is uncertain. Hence, this paper suggests a method for predicting wind power in the short term and analyzing uncertainty using the VDM-TCN approach. This method first uses V
Externí odkaz:
https://doaj.org/article/2ba235d9706d42ce92a5fb47f100a75f
Autor:
Juan Cantizani-Estepa, Sergio Fortes, Javier Villegas, Javier Rasines, Raul Martin Cuerdo, Raquel Barco
Publikováno v:
IEEE Access, Vol 12, Pp 179506-179515 (2024)
The growing complexity of cellular networks makes it harder for network operators to control and manage the system. To ease the management and automatically detect network problems, unsupervised techniques have been put to use. This work proposes a n
Externí odkaz:
https://doaj.org/article/45fd20a4af074debad5c84ea82dc84d0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13308-13323 (2024)
The micropulse multibeam photon-counting laser altimeter significantly improves the sampling density along the orbit while introducing abundant noise. Therefore, noise removal is crucial for the subsequent applications of the photon-counting laser al
Externí odkaz:
https://doaj.org/article/127b064d1428431fa5d7134674bb8fa8
Publikováno v:
电力工程技术, Vol 43, Iss 1, Pp 165-173 (2024)
In this paper, a non-intrusive load identification algorithm for residents based on prior knowledge and statistical learning model is proposed to solve the problem of insufficient electric heating subdivision capability in traditional identification
Externí odkaz:
https://doaj.org/article/413a3be46b054569a3d1c71fb186a5ac
Autor:
Serban Stan, Mohammad Rostami
Publikováno v:
Frontiers in Big Data, Vol 7 (2024)
Semantic segmentation models trained on annotated data fail to generalize well when the input data distribution changes over extended time period, leading to requiring re-training to maintain performance. Classic unsupervised domain adaptation (UDA)
Externí odkaz:
https://doaj.org/article/4cb2ed392b404a71af655166c536fd9a
Publikováno v:
Frontiers in Neurorobotics, Vol 18 (2024)
The quaternion cubature Kalman filter (QCKF) algorithm has emerged as a prominent nonlinear filter algorithm and has found extensive applications in the field of GNSS/SINS integrated attitude determination and positioning system (GNSS/SINS-IADPS) dat
Externí odkaz:
https://doaj.org/article/a32389aa1bf14e7f8bfc8f775c31befb
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 57, Iss 5, Pp 533-544 (2023)
To provide an accurate and objective feedback on rehabilitation training movements and to improve the motivation of rehabilitation patients in rehabilitation training, a motion evaluation method capable of processing continuous human rehabilitation t
Externí odkaz:
https://doaj.org/article/8386372dbfab4fd4a1a66d173ef60e89
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 57, Iss 3, Pp 354-365 (2023)
A novel robot skill learning method using dynamic movement primitive (DMP) and adaptive control is proposed. The existing DMP method learns actions from a single teaching trajectory, and its Gaussian basis function distribution mode is fixed, which i
Externí odkaz:
https://doaj.org/article/b454367dd21a423b92c743e6ee601961