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Neural network correction for heats of formation with a larger experimental training set and new descriptors

文献类型:期刊论文

作者Duan, XM; Li, ZH; Song, GL; Wang, WN; Chen, GH; Fan, KN
刊名Chemical physics letters
出版日期2005-07-10
卷号410期号:1-3页码:125-130
ISSN号0009-2614
DOI10.1016/j.cplett.2005.05.046
通讯作者Fan, kn()
英文摘要A neural-network-based approach was applied to correct the systematic deviations of the calculated heats of formation for 180 organic molecules and led to greatly improved calculation results compared to the first-principles methods [j. chem. phys. 119 (2003) 11501]. in this work, this neural network approach has been improved by using new descriptors obtained from natural bond orbital analysis and an enlarged training set including organic, inorganic molecules and radicals. after the neural network correction, the root-mean-square deviations for the enlarged set decreases from 11.2, 15.2, 327.1 to 4.4, 3.5, 9.5 kcal/mol for the b3lyp/6-31g(d), b3lyp/6-311g(2d,d,p) and hf/6-31g(d) methods, respectively. (c) 2005 elsevier b.v. all rights reserved.
WOS关键词DENSITY-FUNCTIONAL THEORY ; QUADRATIC CONFIGURATION-INTERACTION ; ZERO-POINT ENERGIES ; GAUSSIAN-2 THEORY ; ORGANIC-MOLECULES ; MOLLER-PLESSET ; HARTREE-FOCK ; AB-INITIO ; GEOMETRIES ; FREQUENCIES
WOS研究方向Chemistry ; Physics
WOS类目Chemistry, Physical ; Physics, Atomic, Molecular & Chemical
语种英语
WOS记录号WOS:000230330600025
出版者ELSEVIER SCIENCE BV
URI标识http://www.irgrid.ac.cn/handle/1471x/2374089
专题计算机网络信息中心
通讯作者Fan, KN
作者单位1.Fudan Univ, Ctr Chem Phys, Dept Chem, Shanghai Key Lab Mol Catalysis & Innovat Mat, Shanghai 200433, Peoples R China
2.Chinese Acad Sci, Comp Network Informat Ctr, Virtual Lab Computat Chem, Beijing, Peoples R China
3.Univ Hong Kong, Dept Chem, Hong Kong, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714
Duan, XM,Li, ZH,Song, GL,et al. Neural network correction for heats of formation with a larger experimental training set and new descriptors[J]. Chemical physics letters,2005,410(1-3):125-130.
APA Duan, XM,Li, ZH,Song, GL,Wang, WN,Chen, GH,&Fan, KN.(2005).Neural network correction for heats of formation with a larger experimental training set and new descriptors.Chemical physics letters,410(1-3),125-130.
MLA Duan, XM,et al."Neural network correction for heats of formation with a larger experimental training set and new descriptors".Chemical physics letters 410.1-3(2005):125-130.

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