Improving the Accuracy of Density Functional Theory (DFT) Calculation for Homolysis Bond Dissociation Energies of Y-NO Bond: Generalized Regression Neural Network Based on Grey Relational Analysis and Principal Component Analysis

Improving the Accuracy of Density Functional Theory (DFT) Calculation for Homolysis Bond Dissociation Energies of Y-NO Bond: Generalized Regression Neural Network Based on Grey Relational Analysis and Principal Component Analysis

We propose a generalized regression neural network (GRNN) approach based on grey relational analysis (GRA) and principal component analysis (PCA) (GP-GRNN) to improve the accuracy of density functional theory (DFT) calculation for homolysis bond dissociation energies (BDE) of Y-NO bond. As a demonst...

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Bibliographic Details
Main Authors: Zhong Min Su, Ying Hua Lu, Hui Li, Wei Tao, Ting Gao, Hong Zhi Li
Format: Article
Language:English
Published: MDPI AG 2011-04-01
Series:International Journal of Molecular Sciences
Subjects:
Y-NO bond
homolysis bond dissociation energy
density functional theory
grey relational analysis
principal component analysis
generalized regression neural network
Online Access:http://www.mdpi.com/1422-0067/12/4/2242/

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http://www.mdpi.com/1422-0067/12/4/2242/

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