Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Symmetric Vertical Sinusoid Alignments (SVSA)"'
Publikováno v:
Dyna, Vol 84, Iss 203, Pp 17-23 (2017)
This paper presents the training of an artificial neural network using consumption data measured in the metropolitan network of Valencia, Spain, to estimate the energy consumption of a metro system. After calibration and validation of the neural netw
Externí odkaz:
https://doaj.org/article/53bddf9e613541929c50e7b913f006e7
Autor:
Pineda-Jaramillo, Juan Diego1 jdpineda@unal.edu.co, Salvador-Zuriaga, Pablo1 pabsalzu@ter.upv.es, Insa-Franco, Ricardo1 rinsa@tra.upv.es
Publikováno v:
Dyna. Dec2017, Vol. 84 Issue 203, p17-23. 7p.
Publikováno v:
Urban Rail Transit; Sep2020, Vol. 6 Issue 3, p145-156, 12p
Publikováno v:
Sustainability (2071-1050); Nov2023, Vol. 15 Issue 22, p15834, 29p
Publikováno v:
Urban Rail Transit, Vol 6, Iss 3, Pp 145-156 (2020)
Abstract Minimizing energy consumption is a key issue from both an environmental and economic perspectives for railways systems; however, it is also important to reduce infrastructure construction costs. In the present work, an artificial neural netw
Externí odkaz:
https://doaj.org/article/7e131b7ea6094d2ea12c6daba1dee953
Publikováno v:
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
Urban Rail Transit, Vol 6, Iss 3, Pp 145-156 (2020)
instname
Urban Rail Transit, Vol 6, Iss 3, Pp 145-156 (2020)
[EN] Minimizing energy consumption is a key issue from both an environmental and economic perspectives for railways systems; however, it is also important to reduce infrastructure construction costs. In the present work, an artificial neural network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0832b6b9a4143862b6ee872a992b782f
