Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Paul J. Roebber"'
Publikováno v:
PLoS ONE, Vol 17, Iss 6 (2022)
Using United States National Football League play-by-play data for the 2002–2012 seasons, we train a neural network to predict win probability, based on measures of the game state. This predictor’s performance is comparable to the point spread at
Externí odkaz:
https://doaj.org/article/b5105dc75ef54af3a323df5dfa2a6a37
Autor:
Paul J Roebber
Publikováno v:
PLoS ONE, Vol 16, Iss 1, p e0244941 (2021)
Financial advisors often emphasize asset diversification as a means of limiting losses from investments that perform unexpectedly poorly over a particular time period. One might expect that this perceived wisdom could apply in another high stakes are
Externí odkaz:
https://doaj.org/article/587cdde56808403fbc04cc268a2f99bb
Autor:
Austin R Harris, Paul J Roebber
Publikováno v:
PLoS ONE, Vol 14, Iss 7, p e0220630 (2019)
What determines a team's home advantage, and why does it change with time? Is it something about the rowdiness of the hometown crowd? Is it something about the location of the team? Or is it something about the team itself, the quality of the team or
Externí odkaz:
https://doaj.org/article/ffb571fe4313439d8675eb628eeef199
Autor:
Paul J. Roebber, Stephan Smith
Publikováno v:
Bulletin of the American Meteorological Society.
The National Weather Service (NWS) Office of Science and Technology Integration commissioned a report to assess the status of artificial intelligence (AI) and machine learning (ML) activity within the agency with a view towards identifying existing o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a06a7779f21c6a2aaaa8ba1ecc276b4b
https://doi.org/10.1175/bams-d-22-0181.1
https://doi.org/10.1175/bams-d-22-0181.1
Publikováno v:
Monthly Weather Review.
This study examines extratropical cyclone tracks, central pressure, and maximum intensification rates from a widely used automated cyclone tracking scheme and compares them to the manual tracking of five well-known North Atlantic cyclones whose histo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75bd500fcbe1f5a485ab2d4ac3acc6bc
https://doi.org/10.1175/mwr-d-22-0287.1
https://doi.org/10.1175/mwr-d-22-0287.1
Autor:
Paul J. Roebber
Publikováno v:
Monthly Weather Review. 149:4045-4055
We introduce an adaptive form of postprocessor where algorithm structures are neural networks where the number of hidden nodes and the network training features evolve. Key potential advantages of this system are the flexible, nonlinear mapping capab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8a98775b14ce5088474e3d5552b48f7
https://doi.org/10.1175/mwr-d-21-0089.1
https://doi.org/10.1175/mwr-d-21-0089.1
Publikováno v:
Monthly Weather Review. 148:1951-1970
A statistical–dynamical tropical cyclone (TC) intensity model is developed from a large ensemble of algorithms through evolutionary programming (EP). EP mimics the evolutionary principles of genetic information, reproduction, and mutation to develo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86f4f5457ead03701d0a9108a4ab971d
https://doi.org/10.1175/mwr-d-19-0346.1
https://doi.org/10.1175/mwr-d-19-0346.1
Publikováno v:
PloS one. 17(6)
Using United States National Football League play-by-play data for the 2002–2012 seasons, we train a neural network to predict win probability, based on measures of the game state. This predictor’s performance is comparable to the point spread at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27ea229a2354351bdc520056c02e0c71
https://pubmed.ncbi.nlm.nih.gov/35671316
https://pubmed.ncbi.nlm.nih.gov/35671316
Autor:
Paul J. Roebber, John Crockett
Publikováno v:
Monthly Weather Review. 147:4241-4259
An evolutionary programming postprocessor, using coevolution in a predator–prey ecosystem model, is developed and applied both to 72-h, 2-m temperature forecasts for the conterminous United States and southern Canada and to 60-min nowcasts of conve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14ed50cef14111248573d775d44bf651
https://doi.org/10.1175/mwr-d-19-0063.1
https://doi.org/10.1175/mwr-d-19-0063.1
Publikováno v:
International Journal of Disaster Risk Reduction. 67:102669
Hurricane evacuations involve many interacting physical-social factors and uncertainties that evolve with time as the storm approaches and arrives. Because of these complex and uncertain dynamics, improving the hurricane-forecast-evacuation system re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4984b1495bf7ddf8e9f445b1605f5d08
https://doi.org/10.1016/j.ijdrr.2021.102669
https://doi.org/10.1016/j.ijdrr.2021.102669