Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Alessandro De Gregorio"'
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-17 (2021)
Abstract The homological scaffold leverages persistent homology to construct a topologically sound summary of a weighted network. However, its crucial dependency on the choice of representative cycles hinders the ability to trace back global features
Externí odkaz:
https://doaj.org/article/22a7896fd70b47a09497c2280f34410c
Autor:
Alessandro De Gregorio, Roberto Garra
Publikováno v:
Modern Stochastics: Theory and Applications, Vol 7, Iss 1, Pp 97-112 (2020)
A general class of probability density functions \[ u(x,t)=C{t^{-\alpha d}}{\left(1-{\left(\frac{\| x\| }{c{t^{\alpha }}}\right)^{\beta }}\right)_{+}^{\gamma }},\hspace{1em}x\in {\mathbb{R}^{d}},t>0,\] is considered, containing as particular case the
Externí odkaz:
https://doaj.org/article/255d5b5652fd4a17ad8b707a3bb4ead8
Autor:
Alessandro De Gregorio
Publikováno v:
Modern Stochastics: Theory and Applications, Vol 5, Iss 4, Pp 457-470 (2018)
The nonlocal porous medium equation considered in this paper is a degenerate nonlinear evolution equation involving a space pseudo-differential operator of fractional order. This space-fractional equation admits an explicit, nonnegative, compactly su
Externí odkaz:
https://doaj.org/article/5b3c1f9e3cf64eb784ae9040768d2322
Autor:
Alessandro De Gregorio, Roberto Garra
Publikováno v:
Fractal and Fractional, Vol 5, Iss 2, p 48 (2021)
In this paper, we study diffusion equations involving Hadamard-type time-fractional derivatives related to ultra-slow random models. We start our analysis using the abstract fractional Cauchy problem, replacing the classical time derivative with the
Externí odkaz:
https://doaj.org/article/ed5e60b0e692452b8bfd8de58d4ebd57
Autor:
Roberto Garra, Alessandro De Gregorio
Publikováno v:
Fractal and Fractional, Vol 5, Iss 48, p 48 (2021)
Fractal and Fractional
Volume 5
Issue 2
Fractal and Fractional
Volume 5
Issue 2
In this paper, we study diffusion equations involving Hadamard-type time-fractional derivatives related to ultra-slow random models. We start our analysis using the abstract fractional Cauchy problem, replacing the classical time derivative with the
Autor:
Alessandro De Gregorio, Francesco Vaccarino, Antonio Mastropietro, Giovanni Belingardi, Alberto Ciampaglia, Enrico Busto
Publikováno v:
SAE Technical Paper Series.
Publikováno v:
Scientific Reports
Scientific reports (Nature Publishing Group) 11 (2021): 5355. doi:10.1038/s41598-021-84486-1
info:cnr-pdr/source/autori:Guerra, Marco; De Gregorio, Alessandro; Fugacci, Ulderico; Petri, Giovanni; Vaccarino, Francesco/titolo:Homological scaffold via minimal homology bases/doi:10.1038%2Fs41598-021-84486-1/rivista:Scientific reports (Nature Publishing Group)/anno:2021/pagina_da:/pagina_a:5355/intervallo_pagine:5355/volume:11
Scientific Reports, Vol 11, Iss 1, Pp 1-17 (2021)
Scientific reports (Nature Publishing Group) 11 (2021): 5355. doi:10.1038/s41598-021-84486-1
info:cnr-pdr/source/autori:Guerra, Marco; De Gregorio, Alessandro; Fugacci, Ulderico; Petri, Giovanni; Vaccarino, Francesco/titolo:Homological scaffold via minimal homology bases/doi:10.1038%2Fs41598-021-84486-1/rivista:Scientific reports (Nature Publishing Group)/anno:2021/pagina_da:/pagina_a:5355/intervallo_pagine:5355/volume:11
Scientific Reports, Vol 11, Iss 1, Pp 1-17 (2021)
The homological scaffold leverages persistent homology to construct a topologically sound summary of a weighted network. However, its crucial dependency on the choice of representative cycles hinders the ability to trace back global features onto ind
Autor:
Maria Ferrara, Alessandro De Gregorio, Enrico Fabrizio, Antonio Mastropietro, Francesco Vaccarino, Francesco Della Santa, Ulderico Fugacci, Matteo Bilardo
Publikováno v:
Renewable energy 176 (2021): 590–605. doi:10.1016/j.renene.2021.05.044
info:cnr-pdr/source/autori:Ferrara, Maria; Della Santa, Francesco; Bilardo, Matteo; De Gregorio, Alessandro; Mastropietro, Antonio; Fugacci, Ulderico; Vaccarino, Francesco; Fabrizio, Enrico/titolo:Design optimization of renewable energy systems for NZEBs based on deep residual learning/doi:10.1016%2Fj.renene.2021.05.044/rivista:Renewable energy/anno:2021/pagina_da:590/pagina_a:605/intervallo_pagine:590–605/volume:176
info:cnr-pdr/source/autori:Ferrara, Maria; Della Santa, Francesco; Bilardo, Matteo; De Gregorio, Alessandro; Mastropietro, Antonio; Fugacci, Ulderico; Vaccarino, Francesco; Fabrizio, Enrico/titolo:Design optimization of renewable energy systems for NZEBs based on deep residual learning/doi:10.1016%2Fj.renene.2021.05.044/rivista:Renewable energy/anno:2021/pagina_da:590/pagina_a:605/intervallo_pagine:590–605/volume:176
The design of renewable energy systems for Nearly Zero Energy Buildings (NZEB) is a complex optimization problem. In recent years, simulation-based optimization has demonstrated to be able to support the search for optimal design, but improvements to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8bf6f47af8149d8f1bfa8104aa9db702
http://www.scopus.com/record/display.url?eid=2-s2.0-85107069109&origin=inward
http://www.scopus.com/record/display.url?eid=2-s2.0-85107069109&origin=inward
We consider the random evolution described by the motion of a particle moving on a circle alternating the angular velocities ± c and changing rotation at Poisson random times, resulting in a telegraph process over the circle. We study the analytic p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::354f12d2ed067f919dc252351ced850a
http://arxiv.org/abs/2011.03025
http://arxiv.org/abs/2011.03025