Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

doi:10.1088/1674-1056/19/7/076401

中国物理B ›› 2010, Vol. 19 ›› Issue (7): 76401-076401.doi: 10.1088/1674-1056/19/7/076401

• CONDENSED MATTER: STRUCTURAL, MECHANICAL, AND THERMAL PROPERTIES • 上一篇下一篇

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

王婷婷^ab,李文龙^a,陈章辉^b,缪灵^a

^a Department of Electronic Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;
^bState Key Laboratory for Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences,Beijing 100083, China

出版日期:2010-07-15 发布日期:2010-07-15
基金资助:
Project supported by the National Basic Research Program of China (973 Program) (Grant No. G2009CB929300) and the National Natural Science Foundation of China (Grant No. 60521001 and 60925016).

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

Wang Ting-Ting(王婷婷)^a)b), Li Wen-Long(李文龙)^a), Chen Zhang-Hui(陈章辉)^b)†, and Miao Ling(缪灵)^a)

^a Department of Electronic Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;
^bState Key Laboratory for Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences,Beijing 100083, China

Online:2010-07-15 Published:2010-07-15
Supported by:
Project supported by the National Basic Research Program of China (973 Program) (Grant No. G2009CB929300) and the National Natural Science Foundation of China (Grant No. 60521001 and 60925016).

摘要/Abstract

摘要： The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Abstract: The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Key words: density functional theory, neural network, genetic algorithm, alternate combination

中图分类号: (Neural networks)

84.35.+i

02.60.Pn (Numerical optimization)

王婷婷,李文龙,陈章辉,缪灵. Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network[J]. 中国物理B, 2010, 19(7): 76401-076401.

Wang Ting-Ting(王婷婷), Li Wen-Long(李文龙), Chen Zhang-Hui(陈章辉), and Miao Ling(缪灵). Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network[J]. Chin. Phys. B, 2010, 19(7): 76401-076401.

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Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

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