Emotional responses to energy projects: A new method for modeling and prediction beyond self-reported emotion measure

A considerable amount of studies report that negative emotions evoked by Wind Energy, Nuclear Energy and CO2 Capture and Storage (CCS) can lead to cancellation of the energy project or a delay in policy decisions for its implementation if not adequately addressed. Earlier studies have attempted to s...

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Veröffentlicht in:	Energy (Oxford) Jg. 190; S. 116210
Hauptverfasser:	Buah, Eric, Linnanen, Lassi, Wu, Huapeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.01.2020 Elsevier BV
Schlagworte:	Algorithms Artificial intelligence Carbon dioxide Carbon sequestration case studies CO2 capture and stoarge Computer simulation data collection Decision making Deep neural network algorithm Emotional behavior Emotions energy Energy storage Environmental social science Fuzzy deep learning Fuzzy logic hydrogen Hydrogen-based energy issues and policy Modelling Nuclear capture Nuclear energy Nuclear engineering nuclear power Nuclear reactors prediction Predictions stakeholders Wind power CO2 capture and stoarge Fuzzy logic Fuzzy deep learning Deep neural network algorithm Artificial intelligence Environmental social science
ISSN:	0360-5442, 1873-6785
Online-Zugang:	Volltext
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