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MODELLING THE IONIZATION POTENTIAL OF HALO ALKANES BY NEURAL NETWORK APPROACH

He Liming, Bao Yushi, Lu Hui, Jin Qianyuan

CHINESE JOURNAL OF COMPUTATIONAL PHYSICS 1997, 14 (6): 770-776.

Abstract （270）

PDF （236KB）（1069）

The Back propagation(BP) model of neural network is used to calculate the first ionization potention(IP) of haloalkanes.By optimizing the neural network,the standard deviation of errors of prediction(SDEP) using leave one out method within the known samples is 0.34eV,which is better than the reported predicting and calculating results by PLS.

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DETERMINATION OF THE BOND LENGTH OF DIATOMIC MOLECULE BY USING NEURAL NETWORK APPROACH

He liming, Chen Kongchang

CHINESE JOURNAL OF COMPUTATIONAL PHYSICS 1996, 13 (2): 243-248.

Abstract （266）

PDF （367KB）（1034）

By using the back-propagation (BP) model of neural network,the bond length of diatomic molecule is determinated.Slater atomic radius,Pauling electronegativity,major group and cycle numbers of the periodic table,etc.,are used as features.The calculated and predicted results of neural network appear to be better than those of reported calculations.

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