Zobrazeno 1 - 10
of 268
pro vyhledávání: '"Emmanouil N, Anagnostou"'
Autor:
Qing Yang, Xinyi Shen, Kang He, Qingyuan Zhang, Sean Helfrich, William Straka, Josef M. Kellndorfer, Emmanouil N. Anagnostou
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-8 (2024)
Abstract On June 6, 2023, the Kakhovka Dam in Ukraine experienced a catastrophic breach that led to the loss of life and substantial economic values. Prior to the breach, the supporting structures downstream of the spillway had shown signs of being c
Externí odkaz:
https://doaj.org/article/cd0ea36190b94f2b973bc00ef99c8f1c
Publikováno v:
IEEE Access, Vol 12, Pp 126285-126295 (2024)
Severe weather is a leading cause of electric distribution network failures and customer outages. Predictive modelling of customer outages can mitigate the economic and personal impact of adverse weather but is challenging due to the diverse causes a
Externí odkaz:
https://doaj.org/article/2f32d245ccd44b90aa0c8ac8093f7c3e
Publikováno v:
Energy Reports, Vol 10, Iss , Pp 4148-4169 (2023)
In the United States, weather-related power outages cost the economy tens of billions annually, and there has been an upward trend in billion-dollar disasters over the last two decades. Thus, it is of growing importance to be able to predict outages
Externí odkaz:
https://doaj.org/article/4d8df144a8284a54bf2fa87aa80a6959
Publikováno v:
Journal of Flood Risk Management, Vol 16, Iss 2, Pp n/a-n/a (2023)
Abstract The estimation of extreme flood frequency for ungauged or poorly gauged catchments is a longstanding problem of great practical importance. Simulated streamflow derived from distributed hydrological models can be used to address this issue,
Externí odkaz:
https://doaj.org/article/8bc32c782f5547a6ab5892dad467674c
Publikováno v:
Forecasting, Vol 3, Iss 3, Pp 501-516 (2021)
Weather-related power outages affect millions of utility customers every year. Predicting storm outages with lead times of up to five days could help utilities to allocate crews and resources and devise cost-effective restoration plans that meet the
Externí odkaz:
https://doaj.org/article/e8f48cf0e7174e60af62fb0fd07de6be
Publikováno v:
Earth's Future, Vol 10, Iss 3, Pp n/a-n/a (2022)
Abstract Given the rapidly changing climate, accurate spatiotemporal information on the evolution of extreme rainfall events is required for flood risk assessment and the design of resilient infrastructure. Consequently, various research efforts have
Externí odkaz:
https://doaj.org/article/8503876fadc24f46a2ec1c7134c561a8
Publikováno v:
IEEE Access, Vol 8, Pp 60029-60042 (2020)
The accuracy of machine learning-based power outage prediction models (OPMs) is sensitive to how well event severity is represented in their training datasets. Unbalanced or overly dispersed event severity can result in random errors in outage predic
Externí odkaz:
https://doaj.org/article/09f41892f0c24696b0454e21fced639b
Autor:
Diego Cerrai, David W. Wanik, Md Abul Ehsan Bhuiyan, Xinxuan Zhang, Jaemo Yang, Maria E. B. Frediani, Emmanouil N. Anagnostou
Publikováno v:
IEEE Access, Vol 7, Pp 29639-29654 (2019)
This paper introduces new developments in an outage prediction model (OPM) for an electric distribution network in the Northeastern United States and assesses their significance to the OPM performance. The OPM uses regression tree models fed by numer
Externí odkaz:
https://doaj.org/article/1ae0567f09f14719905574667b9cb0da
Publikováno v:
Tecnología y ciencias del agua, Vol 9, Iss 3, Pp 128-142 (2018)
A key area of research in hydrologic modeling is the prediction of flood response in complex urban basins with hydraulic structures such as pump stations, canals, culverts, and spillways. The prediction of the basin’s response to heavy rainfall is
Externí odkaz:
https://doaj.org/article/39488619890c4e4aacd0ee58217ddd17
While various research efforts investigate the direct effects of climate change on hydrometeorological variables, the incidental consequences of extreme rainfall trends on the flow capacity of open channels remains an open question. Hydrological mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c33861a348b05b7cf90fa2f1342fda4
https://doi.org/10.5194/egusphere-egu23-6081
https://doi.org/10.5194/egusphere-egu23-6081
