Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Gi-Wook Cha"'
Autor:
Gi-Wook Cha, Won-Hwa Hong
Publikováno v:
Journal of The Korean Society of Living Environmental System. 30:20-29
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a711b5fb426ca0f9c4110a8038fa6462
https://doi.org/10.21086/ksles.2023.2.30.1.20
https://doi.org/10.21086/ksles.2023.2.30.1.20
Publikováno v:
Sustainability; Volume 15; Issue 13; Pages: 10163
Smart management of construction and demolition (C&D) waste is imperative, and researchers have implemented machine learning for estimating waste generation. In Korea, the management of demolition waste (DW) is important due to old buildings, and it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::2878d2cdf359a32b59457cc64ce157d2
Publikováno v:
Sustainability
Volume 15
Issue 4
Pages: 3691
Volume 15
Issue 4
Pages: 3691
Owing to the rapid increase in construction and demolition (C&D) waste, the information of waste generation (WG) has been advantageously utilized as a strategy for C&D waste management. Recently, artificial intelligence (AI) has been strategically em
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edecfc4fa05481316fb3900c38533efb
Publikováno v:
International Journal of Environmental Research and Public Health
Volume 20
Issue 4
Pages: 3159
Volume 20
Issue 4
Pages: 3159
Construction and demolition waste accounts for a sizable proportion of global waste and is harmful to the environment. Its management is therefore a key challenge in the construction industry. Many researchers have utilized waste generation data for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c38a12ec535f38c42d331c7395b98c71
Publikováno v:
International Journal of Environmental Research and Public Health; Volume 20; Issue 1; Pages: 107
Owing to a rapid increase in waste, waste management has become essential, for which waste generation (WG) information has been effectively utilized. Various studies have recently focused on the development of reliable predictive models by applying a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6536c3f5d2002c857726f176bd6ae7cd
Publikováno v:
Journal of Cleaner Production. 375:134096
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88bae970938276c0bc5af549c7cb9f18
https://doi.org/10.1016/j.jclepro.2022.134096
https://doi.org/10.1016/j.jclepro.2022.134096
Publikováno v:
International Journal of Environmental Research and Public Health
Volume 18
Issue 16
International Journal of Environmental Research and Public Health, Vol 18, Iss 8530, p 8530 (2021)
Volume 18
Issue 16
International Journal of Environmental Research and Public Health, Vol 18, Iss 8530, p 8530 (2021)
Construction and demolition waste (DW) generation information has been recognized as a tool for providing useful information for waste management. Recently, numerous researchers have actively utilized artificial intelligence technology to establish a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1753133f4b66066e4a29784ec351dab
Autor:
Young-Chan Kim, Won-Hwa Hong, Young Min Kim, Gi-Wook Cha, Jung-Ha Hwang, Hyeun Jun Moon, Won-Jun Park
Publikováno v:
International Journal of Environmental Research and Public Health
International Journal of Environmental Research and Public Health, Vol 17, Iss 6997, p 6997 (2020)
Volume 17
Issue 19
International Journal of Environmental Research and Public Health, Vol 17, Iss 6997, p 6997 (2020)
Volume 17
Issue 19
Recently, artificial intelligence (AI) technologies have been employed to predict construction and demolition (C&
D) waste generation. However, most studies have used machine learning models with continuous data input variables, applying algo
D) waste generation. However, most studies have used machine learning models with continuous data input variables, applying algo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63d04fb7f09bc983f7d67c6dd320a43f
https://pubmed.ncbi.nlm.nih.gov/32987874
https://pubmed.ncbi.nlm.nih.gov/32987874
Autor:
Karel Van Acker, Mª Desirée Alba-Rodríguez, Cecilia Azevedo, Maria Chiara Bignozzi, Giuseppe Bonifazi, Mingli Cao, Isidro A. Carrascal, Gi-Wook Cha, Prinya Chindaprasirt, Ana Cimentada, Raffaele Cioffi, Francesco Colangelo, Nele De Belie, Mercedes del Río Merino, Andrea Di Maria, Yining Ding, Huiwen Dong, Christian John Engelsen, Miren Etxeberria, Johan Eyckmans, Ilenia Farina, Alberto Ferraro, José-Luis Gálvez-Martos, Julia García-González, Justo García-Navarro, Fernando López Gayarre, Patrizia Ghisellini, Aliakbar Gholampour, Jesús Suárez González, M. Ignacio Guerra-Romero, Zhanggen Guo, Asad Hanif, W.H. Hong, Ioan-Robert Istrate, Tianxun Jiang, Ana Jiménez-Rivero, Andrés Juan-Valdés, Abbaas I. Kareem, Young-Chan Kim, Xiangkun Kong, Alexander Koutamanis, K.P.V. Lafayette, Stefania Manzi, Madelyn Marrero, Amelia Marshall, Ivan Moccia, H.J. Moon, Hamid Nikraz, Togay Ozbakkaloglu, F. Pacheco-Torgal, D.H.F. Paz, Carlos López-Colina Pérez, Antonella Petrillo, Juan A. Polanco, César Porras-Amores, Julia Mª Morán-del Pozo, Cristina Rivero-Camacho, Desirée Rodríguez-Robles, José A. Sainz-Aja, Vanchai Sata, Miguel A. Serrano López, Silvia Serranti, Jesús Setién, Rafat Siddique, Nagaratnam Sivakugan, Marija Šljivić-Ivanović, Ivana Smičiklas, M.C.M. Sobral, Jaime Solís-Guzmán, Yan Sun, C. Thomas, An Tu, Rabin Tuladhar, Sergio Ulgiati, Paola Villoria-Sáez, Jing Zhang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94be43e375ebf1c31ff710391e5ec512
https://doi.org/10.1016/b978-0-12-819055-5.09990-3
https://doi.org/10.1016/b978-0-12-819055-5.09990-3
