A machine learning approach for mapping the very shallow theoretical geothermal potential

Overview of attention for article published in Geothermal Energy, July 2019

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dimensions_citation: 32 Dimensions

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So far, Dimensions has found 32 publications that cite this research output.

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The most recent citing publications are shown below. View all 32 publications that cite this research output on Dimensions.

Techno-economic analysis of electrical flexibility in combustion-based district heating systems: A Swiss case study

Article in International Journal of Electrical Power & Energy Systems (June 2024)

Verification of an open-source Python library for the simulation of district heating networks with complex topologies

Article in Energy (March 2024)

Machine learning solutions for renewable energy systems: Applications, challenges, limitations, and future directions

Article in Journal of Environmental Management (February 2024)