Zobrazeno 1 - 4 of 4 pro vyhledávání: '"Steve Wattam"'
1
Knowledge Organization Systems for Systematic Chemical Assessments
Autor: Sean Watford, Andrew D. Kraft, Michelle M. Angrish, Stephen W. Edwards, Taylor Wolffe, Steve Wattam, Paul Whaley, Andrew Shapiro, Kate Nyhan
Publikováno v: Environmental Health Perspectives
BACKGROUND: Although the implementation of systematic review and evidence mapping methods stands to improve the transparency and accuracy of chemical assessments, they also accentuate the challenges that assessors face in ensuring they have located a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3eea674196d6e3403ad18948cefbee9d
https://doi.org/10.1289/EHP6994
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2
Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review
Autor: Aristides Kiprakis, Desen Kirli, Steve Wattam, Valentin Robu, Sonam Norbu, Ioannis Antonopoulos, Sergio Elizondo-Gonzalez, Benoit Couraud, David Flynn
Publikováno v: Renewable and Sustainable Energy Reviews, 130
Antonopoulos, I, Robu, V, Couraud, B, Kirli, D, Norbu, S, Kiprakis, A, Flynn, D, Elizondo gonzález, S I & Wattam, S 2020, ' Artificial Intelligence and Machine Learning Approaches to Energy Demand-Side Response: A Systematic Review ', Renewable and Sustainable Energy Reviews, vol. 130, 109899 . https://doi.org/10.1016/j.rser.2020.109899
Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility, and hence improve the reliability of energy systems in a cost-effective way. Yet, the high complexity of the tasks associated with DR, combined w
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe2df6225a8ac1faca11cd92f6d2c2bb
https://ir.cwi.nl/pub/30375
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3
Adversarial Machine Learning in Smart Energy Systems
Autor: Angelos K. Marnerides, Steve Wattam, Andy Molineux, Utz Roedig, Martin Bor
Publikováno v: e-Energy
Smart Energy Systems represent a radical shift in the approach to energy generation and demand, driven by decentralisation of the energy system to large numbers of low-capacity devices. Managing this flexibility is often driven by machine learning, a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e4024da33182060672e848c8e341e5c8
https://doi.org/10.1145/3307772.3330171
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