Network science and explainable AI-based life cycle management of sustainability models

Model-based assessment of the potential impacts of variables on the Sustainable Development Goals (SDGs) can bring great additional information about possible policy intervention points. In the context of sustainability planning, machine learning techniques can provide data-driven solutions througho...

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Veröffentlicht in:	PloS one 2024-06, Vol.19 (6), p.e0300531
Hauptverfasser:	Ipkovich, Ádám, Czvetkó, Tímea, A Acosta, Lilibeth, Lee, Sanga, Nzimenyera, Innocent, Sebestyén, Viktor, Abonyi, János
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Biology and Life Sciences Case studies Changing environments Computer and Information Sciences Conservation of Natural Resources - methods Data analysis Data science Decision making Earth Sciences Ecology and Environmental Sciences Economic growth Environment models Environmental changes Explainable artificial intelligence Fluid dynamics Forecasts and trends Humans Hungary Intervention Learning algorithms Life cycles Machine Learning Models, Theoretical Network analysis Physical Sciences Physical simulation Renewable resources Research and Analysis Methods Social networks Structural equation modeling Sustainability Sustainability management Sustainable Development Variables Water resources Water reuse Water stress
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