Integrating computational intelligence and predictive modeling for sustainable environmental and energy systems

The transition towards sustainable resource management and renewable energy systems requires robust analytical tools and predictive models. Environmental and energy modeling plays a crucial role in understanding complex ecological and energy systems, allowing for optimized resource allocation, impact assessment, and the development of innovative green technologies. As global energy demands rise, integrating advanced computational techniques—such as machine learning, deep learning, and advanced statistical forecasting—into environmental and energy sectors becomes indispensable for achieving the Sustainable Development Goals (SDGs).This Research Topic aims to gather cutting-edge research on the application of mathematical, computational, and predictive modeling applied to environmental and energy systems. We are particularly interested in interdisciplinary approaches that bridge the gap between chemical engineering, environmental science, and data-driven technologies. Areas of interest include, but are not limited to, solar forecasting, optimization of energy storage systems (such as supercapacitors), mass transport phenomena in environmental contexts, and the life-cycle assessment of sustainable materials.By bringing together experts from diverse fields, this collection will highlight how advanced modeling techniques can mitigate environmental impacts and enhance the efficiency of renewable energy systems. We welcome Original Research, Reviews, and Perspectives that address the challenges of sustainable land use, natural resource management, and the integration of smart technologies in energy networks.Themes of interest include:• Machine learning and deep learning applications in energy forecasting (e.g., solar, wind).• Computational modeling of mass transport and chemical processes for environmental remediation.• Modeling and optimization of advanced energy storage devices.• Data-driven approaches for environmental impact assessments and sustainable land use.• Techno-economic and life-cycle modeling of renewable energy systems and sustainable materials.Ultimately, the goal is to equip policymakers, engineers, and researchers with the necessary computational frameworks to make informed decisions that align with global sustainability targets. We encourage submissions that not only present novel modeling methodologies but also demonstrate practical applications and case studies with real-world implications.Note: Papers which are focused on the mathematical/ modelling methodology without a clear link to sustainable resources and energy systems are not considered in scope for this Topic Topic editors: Isnaldo Barbosa, SOUSA, Henrique Viana EHV, Juliana Roberta Theodoro De Lima, Bin Chen Source: https://www.frontiersin.org/research-topics/83428/integrating-computational-intelligence-and-predictive-modeling-for-sustainable-environmental-and-energy-systems