Zobrazeno 1 - 10
of 213
pro vyhledávání: '"V. A. Samaranayake"'
Publikováno v:
PLoS ONE, Vol 18, Iss 5, p e0285769 (2023)
A serially dependent Poisson process with time-varying zero-inflation is proposed. Such formulations have the potential to model count data time series arising from phenomena such as infectious diseases that ebb and flow over time. The model assumes
Externí odkaz:
https://doaj.org/article/4fba91a665e14b64878989adc312da02
Autor:
Ruwan Weerasinghe
Publikováno v:
Journal of the National Science Foundation of Sri Lanka. 35:211
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5ada026d805500eb7ad6d16287d991a
https://doi.org/10.4038/jnsfsr.v35i3.2022
https://doi.org/10.4038/jnsfsr.v35i3.2022
Publikováno v:
PLoS ONE, Vol 13, Iss 2, p e0193247 (2018)
Human exposure to volatile organic compounds (VOCs) via vapor intrusion (VI) is an emerging public health concern with notable detrimental impacts on public health. Phytoforensics, plant sampling to semi-quantitatively delineate subsurface contaminat
Externí odkaz:
https://doaj.org/article/b3f9e6fe7b80446fb0a316f5ccb13287
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 32:4323-4333
In this article, a novel learning methodology is introduced for the problem of classification in the context of high-dimensional data. In particular, the challenges introduced by high-dimensional data sets are addressed by formulating a $L_{1}$ regul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::083fbc9f7898bf3c05582fe0e8c0e7a2
https://doi.org/10.1109/tnnls.2020.3017434
https://doi.org/10.1109/tnnls.2020.3017434
A serially dependent Poisson process with time-varying zero-inflation is proposed. Such formulations have the potential to model count data time series arising from phenomena such as infectious diseases that ebb and flow over time. The model assumes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e84f18584f114ee02b27319db558a3a
http://arxiv.org/abs/2207.10114
http://arxiv.org/abs/2207.10114
A Multi-Step Approach to Modeling the 24-hour Daily Profiles of Electricity Load using Daily Splines
Autor:
Abdelmonaem Jornaz, V. A. Samaranayake
Publikováno v:
Energies, Vol 12, Iss 21, p 4169 (2019)
Forecasting of real-time electricity load has been an important research topic over many years. Electricity load is driven by many factors, including economic conditions and weather. Furthermore, the demand for electricity varies with time, with diff
Externí odkaz:
https://doaj.org/article/c6a88abcc62b422a9673e9c6b80d9887
Publikováno v:
INNS Conference on Big Data
In this brief, heterogeneity and noise in big data are shown to increase the generalization error for a traditional learning regime utilized for deep neural networks (deep NNs). To reduce this error, while overcoming the issue of vanishing gradients,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0113dc07e58a461fd7b2416ba6ffae6c
https://doi.org/10.1109/tnnls.2019.2920964
https://doi.org/10.1109/tnnls.2019.2920964
Publikováno v:
INNS Conference on Big Data
In this paper, a novel dimension-reduction approach is presented to overcome challenges such as nonlinear relationships, heterogeneity, and noisy dimensions. Initially, the $p$ p attributes in the data are first organized into random groups. Next, to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e38c09d4dc7a7570ed20ed7b2b48af6b
https://doi.org/10.1109/tkde.2018.2876848
https://doi.org/10.1109/tkde.2018.2876848
Publikováno v:
Stat. 10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8e5e4a90e5278941836344e2f540292
https://doi.org/10.1002/sta4.345
https://doi.org/10.1002/sta4.345
Publikováno v:
Journal of Non-Crystalline Solids. 495:107-116
Mathematical models for the chemical durability–composition relation for 5-component iron phosphate glasses, containing a nuclear waste similar to that of the high sulfate (~17 wt%), high soda (~80 wt%) Hanford AZ 102 LAW, have been developed using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69d80458a0cf849a16854a67b8b73b28
https://doi.org/10.1016/j.jnoncrysol.2018.05.007
https://doi.org/10.1016/j.jnoncrysol.2018.05.007