Machine Learning Accelerated Genetic Algorithms for Computational Materials Search

Autor:	Steen Lysgaard, Paul C. Jennings, Jens Strabo Hummelshøj, Thomas Bligaard, Tejs Vegge
Rok vydání:	2018
Popis:	A machine learning model is used as a surrogate fitness evaluator in a genetic algorithm (GA) optimization of the atomic distribution of Pt-Au nanoparticles. The machine learning accelerated genetic algorithm (MLaGA) yields a 50-fold reduction of required energy calculations compared to a traditional GA.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2436fe51933223b5fb3b972496e8a60 https://doi.org/10.26434/chemrxiv.7411172.v1 Zobrazit plný text záznamu