Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms

This work proposes several machine learning models that predict B3LYP-D4/def-TZVP outputs from HF-3c outputs for supramolecular structures. The data set consists of 1031 entries of dimer, trimer, and tetramer cyclic structures, containing both molecules with heteroatoms in the ring and without. Six...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Saadiallakh Normatov (20682324) (author)
مؤلفون آخرون:	Pavel V. Nesterov (11027409) (author), Timur A. Aliev (12426758) (author), Alexandra A. Timralieva (11027412) (author), Alexander S. Novikov (1616380) (author), Ekaterina V. Skorb (2060947) (author)
منشور في:	2025
الموضوعات:	Biophysics Biochemistry Neuroscience Physiology Biotechnology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified statistical analysis shows density functional theory data set consists tetramer cyclic structures machine learning models best prediction values best models supramolecular structures tzvp outputs three groups predict b3lyp neural networks layer perceptron good correlation dipole moment computational methods band gap bad correlation 3c outputs 1031 entries
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Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms

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