Improving the Accuracy of Low Level Density Functional Theory Calculation for Absorption Energies: The Least Squares Support Vector Machine

Least squares support vector machines (LS-SVM) was introduced to improve the calculation accuracy of low level density functional theory. As a demonstration, this combined low level quantum mechanical calculation with LS-SVM correction approach has been applied to evaluate the absorption energies of...

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Bibliographic Details
Main Authors: Ting Gao, Dong-Bing Pu, Hui Li, Ying-Hua Lu, Hai-Bin Li, Hong-Zhi Li, Zhong-Min Su
Format: Conference Proceeding
Language:English
Subjects:
Absorption
absorption energies
Chemicals
Chemistry
Density functional theory
Least squares methods
Machine intelligence
Machine learning
Neural networks
quantum mechanical calculation
Quantum mechanics
Support vector machines
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Summary:Least squares support vector machines (LS-SVM) was introduced to improve the calculation accuracy of low level density functional theory. As a demonstration, this combined low level quantum mechanical calculation with LS-SVM correction approach has been applied to evaluate the absorption energies of 160 organic molecules. After LS-SVM correction, the RMS deviations of the calculated absorption energies reduce from 0.95 to 0.16 eV for B3LYP/STO-3G methods. And, this LS-SVM/B3LYP/STO-3G is a excellent method to predict absorption energies and can be used as an alternative to experimental measurements and high-accurate quantum chemical calculations to obtain the value of absorption energies reliably and efficiently.
DOI:10.1109/ICICTA.2010.862