iEMSs 2022 Conference - Brussels, Belgium

iEMSs 2022 - Session B.3

Hybrid approaches to analysis, modelling and prediction of environmental data in support of sustainability

Stream    : B - Processing and Visualizing Environmental Information from Big Data, Data mining, GIS, and Remote sensing

Session Leader: Peter A. Khaiter (York University, Canada), Marina G. Erechtchoukova (York University, Canada)

The session invites original contributions on a wide range of environmental applications, such as renewable energy, resource management, ecosystem services, land and forest use, agriculture and food production, water cycle, air quality, climate change and its societal impacts based on hybrid approaches. The techniques include, but are not limited to, exploratory [Big] data analysis, dataset summarization, explainable feature engineering, hybrid models and joint prediction and explanation, backward propagation and proxy models, intelligent data analysis and its combination with process-based simulations and computational modelling, exploratory and confirmatory analysis. Hybrid frameworks and techniques, success stories of their application and lessons learned are of special interest.