المؤلفون: Santosh S. Sutar (11608432), Suvarna M. Patil (11608435), Sunil J. Kadam (11608438), Rajanish K. Kamat (4919062), Deok-kee Kim (1444282), Tukaram D. Dongale (4919056)

مصطلحات موضوعية: Biotechnology, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, shrinking manufacturing windows, popular photoactive material, decision tree algorithm, also employed supervised, hydrothermally synthesized zno, hydrothermally grown zno, sensitized solar cells, hydrothermally synthesized dsscs, designing efficient dsscs, using random forest, different synthesis parameters, applying statistical analysis, learning techniques dye, cost solar cells, solar cells, random forest, zno dsscs, evaluate zno, based dye, learning technique, learning algorithms, significant insights, said period, said know, results substantiate, regression trees, recommend extending

Relation: https://figshare.com/articles/journal_contribution/Analysis_and_Prediction_of_Hydrothermally_Synthesized_ZnO-Based_Dye-Sensitized_Solar_Cell_Properties_Using_Statistical_and_Machine-Learning_Techniques/16879006

الاتاحة: https://doi.org/10.1021/acsomega.1c04521.s001