Zobrazeno 1 - 10
of 5 404
pro vyhledávání: '"multivariate time-series"'
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-14 (2024)
Abstract The particulate matter (PM)2.5 forecasting has been being advanced with the development of deep learning methods. However, most of them do not consider the active population exposed to air pollution. We propose to apply a population-based ce
Externí odkaz:
https://doaj.org/article/a343488d4ffc46f0b33c3792eecfa5e6
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract In recent years, the uncertainty of weather conditions and the impact of future climate change on building energy assessment has received increasing attention. As an important part of these studies, several types of methods for generating st
Externí odkaz:
https://doaj.org/article/f63c831cfcca4da592de64586eccfffb
Autor:
Jie Yu, Huimin Wang, Miaoshuang Chen, Xinyue Han, Qiao Deng, Chen Yang, Wenhui Zhu, Yue Ma, Fei Yin, Yang Weng, Changhong Yang, Tao Zhang
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Background Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for constructing cross-regional i
Externí odkaz:
https://doaj.org/article/cffd13fea3864a8e865225bc1811ea12
Autor:
Bubryur Kim, K. R. Sri Preethaa, Sujeen Song, R. R. Lukacs, Jinwoo An, Zengshun Chen, Euijung An, Sungho Kim
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-37 (2024)
Abstract The construction industry substantially contributes to the economic growth of a country. However, it records a large number of workplace injuries and fatalities annually due to its hesitant adoption of automated safety monitoring systems. To
Externí odkaz:
https://doaj.org/article/81c64d9d4c39449cae3d17a37e5c47e4
Autor:
Abhidnya Patharkar, Jiajing Huang, Teresa Wu, Erica Forzani, Leslie Thomas, Marylaura Lind, Naomi Gades
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Most current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative m
Externí odkaz:
https://doaj.org/article/3ab533fc6a494db5b12d44d5ce6d7330
Publikováno v:
工程科学学报, Vol 46, Iss 6, Pp 1108-1119 (2024)
The blowing process in converter steelmaking at the blowing stage mainly includes oxygen supply, slag discharge, and bottom blowing. The stability of the blowing process directly affects the quality of the molten steel at the end. The traditional sta
Externí odkaz:
https://doaj.org/article/cdfa8668f4a8492a974dd904105db4ab
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-14 (2024)
Abstract The paper proposes a hybrid algorithm for forecasting multiple correlated time-series data, which consists of two main steps. First, it employs a multivariate Bayesian structural time series (MBSTS) approach as a base step. This method allow
Externí odkaz:
https://doaj.org/article/b099cfd7fb14457d9b04d0a5f6819763
Publikováno v:
Earth and Space Science, Vol 11, Iss 10, Pp n/a-n/a (2024)
Abstract Antarctic sea ice, a key component in the complex Antarctic climate system, is an important driver and indicator of the global climate. In the relatively short satellite‐observed period from 1979 to 2022 the sea ice extent has continuously
Externí odkaz:
https://doaj.org/article/f570c52cfdec4c1f97f50fecad941021
Autor:
Haocheng Wu, Ming Xue, Chen Wu, Qinbao Lu, Zheyuan Ding, Xinyi Wang, Tianyin Fu, Ke Yang, Junfen Lin
Publikováno v:
Frontiers in Public Health, Vol 12 (2024)
BackgroundChina is one of the main epidemic areas of scrub typhus, and Zhejiang Province, which is located in the coastal area of southeastern China, is considered a key region of scrub typhus. However, there may be significant bias in the number of
Externí odkaz:
https://doaj.org/article/5b9428f454ba46df9514135c5ce34e84
Autor:
Younghoo Kim, Heeyeun Yoon
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 133, Iss , Pp 104113- (2024)
Urban public open spaces (POS) are pivotal in sustainable urban planning, recognized for their positive impacts on the health of residents and environments. However, understanding their physical features in detail via remote sensing remains challengi
Externí odkaz:
https://doaj.org/article/7cb27e1786c04c8884b5066adf0208a4