Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...
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Machine learning framework boosts residential electricity clustering for demand-response
The National Technical University of Athens (NTUA), one of the DEDALUS scientific partners, has completed a study on grouping residential electricity consumers, based on their historical electricity ...
In materials science, substances are often classified based on defining factors such as their elemental composition or crystalline structure. This classification is crucial for advances in materials ...
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