Predicting the band gap of ZnO quantum dots via supervised machine learning models
Paul Rossener Regonia, Christian Mark Pelicano, Ryosuke Tani, Atsushi Ishizumi, Hisao Yanagi, Kazushi Ikeda
Topics & Concepts
Mean squared errorComputer scienceArtificial neural networkMachine learningArtificial intelligenceMean absolute errorRegressionKernel (algebra)Band gapSupervised learningAlgorithmMaterials scienceMathematicsOptoelectronicsStatisticsCombinatoricsZnO doping and propertiesMachine Learning in Materials ScienceGas Sensing Nanomaterials and Sensors