Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Surajate Boonya-aroonnet"'
Autor:
Lattawit Kulanuwat, Chantana Chantrapornchai, Montri Maleewong, Papis Wongchaisuwat, Supaluk Wimala, Kanoksri Sarinnapakorn, Surajate Boonya-aroonnet
Publikováno v:
Water, Vol 13, Iss 13, p 1862 (2021)
Water level data obtained from telemetry stations typically contains large number of outliers. Anomaly detection and a data imputation are necessary steps in a data monitoring system. Anomaly data can be detected if its values lie outside of a normal
Externí odkaz:
https://doaj.org/article/c8e7ac1955b448129db51881b3f7ba28
Autor:
Miguel Laverde-Barajas, Gerald A. Corzo, Ate Poortinga, Farrukh Chishtie, Chinaporn Meechaiya, Susantha Jayasinghe, Peeranan Towashiraporn, Amanda Markert, David Saah, Lam Hung Son, Sothea Khem, Surajate Boonya-Aroonnet, Winai Chaowiwat, Remko Uijlenhoet, Dimitri P. Solomatine
Publikováno v:
Remote Sensing, Vol 12, Iss 21, p 3538 (2020)
Advances in near real-time rainstorm prediction using remote sensing have offered important opportunities for effective disaster management. However, this information is subject to several sources of systematic errors that need to be corrected. Tempo
Externí odkaz:
https://doaj.org/article/d8bbbca1357e4fe6a33ef15c3fb08be8
Autor:
Laddaporn Ruangpan, Mosaab Mahgoub, Yared Abayneh Abebe, Zoran Vojinovic, Surajate Boonya-aroonnet, Arlex Sanchez Torres, Sutat Weesakul
The intensity and frequency of hydro-meteorological hazards have increased due to fast-growing urbanisation activities and climate change. Hybrid approaches that combine grey infrastructure and Nature-Based Solutions (NBSs) have been applied as an ad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::db9a5b22dcc5d341c103fbb02ca3d922
https://zenodo.org/record/8082894
https://zenodo.org/record/8082894
Autor:
Kasemsan Manomaiphiboon, Surajate Boonya-Aroonnet, Kanoksri Sarinnapakorn, Nishit Aman, Nosha Assareh, Kritanai Torsri, Devkota, Bikash, Muanfun Inerb, Sawangwattanaphaibun, Rati, Aungkana Jinvong
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::485fa35387ba50d772de0a52bc996b3f
Autor:
Kasemsan Manomaiphiboon, Surajate Boonya-Aroonnet, Kanoksri Sarinnapakorn, Nishit Aman, Thi, Hoang, Eakkachai Kokkaew, Sawangwattanaphaibun, Rati, Aungkana Jinvong, Kritanai Torsri, Nosha Assareh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca248c664009857a7273ad2b6ef01a4d
Autor:
Kanoksri Sarinnapakorn, Montri Maleewong, Chantana Chantrapornchai, Papis Wongchaisuwat, Surajate Boonya-aroonnet, Supaluk Wimala, Lattawit Kulanuwat
Publikováno v:
Water, Vol 13, Iss 1862, p 1862 (2021)
Water
Volume 13
Issue 13
Water
Volume 13
Issue 13
Water level data obtained from telemetry stations typically contains large number of outliers. Anomaly detection and a data imputation are necessary steps in a data monitoring system. Anomaly data can be detected if its values lie outside of a normal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64ba13b7c7ecd913941ca9cc8f5ceb9f
https://doi.org/10.3390/w13131862
https://doi.org/10.3390/w13131862
Autor:
Surajate Boonya-aroonnet, Tomohiro Okadera, Danutawat Tipayarom, Wilasinee Yoochatchaval, Winai Chaowiwat
Publikováno v:
Journal of Industrial Ecology. 20:484-493
It is predicted that energy requirements in developing countries will increase global water consumption as a result of implementation of new power generation systems, and to population growth of the middle classes. Thus, it is anticipated that increa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3201e4cd92d49540e11b396da5932890
https://doi.org/10.1111/jiec.12387
https://doi.org/10.1111/jiec.12387
Autor:
Farrukh Chishtie, C. Meechaiya, Ate Poortinga, David Saah, Sothea Khem, Gerald Corzo, Miguel Laverde-Barajas, Surajate Boonya-aroonnet, P. Towashiraporn, Lam Hung Son, Dimitri Solomatine, Winai Chaowiwat, Amanda Markert, S. Jayasinghe, Remko Uijlenhoet
Publikováno v:
Remote Sensing, 12(21)
Remote Sensing 12 (2020) 21
Remote Sensing
Volume 12
Issue 21
Remote Sensing, Vol 12, Iss 3538, p 3538 (2020)
Remote Sensing 12 (2020) 21
Remote Sensing
Volume 12
Issue 21
Remote Sensing, Vol 12, Iss 3538, p 3538 (2020)
Advances in near real-time rainstorm prediction using remote sensing have offered important opportunities for effective disaster management. However, this information is subject to several sources of systematic errors that need to be corrected. Tempo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7800620c0da173e4c1b931375372f676
https://doi.org/10.3390/rs12213538
https://doi.org/10.3390/rs12213538
Supplement 1, 11, NARESUAN UNIVERSITY ENGINEERING JOURNAL
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1de6c8955aeee6d09277a5b68f85b3fa