The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction ...The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction energy based on quantum mechanics can not be merged into molecular dynamic simulation for a long time scale.A deep learning framework,deep tensor neural network,is applied to predict the interaction energy of three organic related systems within the quantum mechanics level of accuracy.The geometric structure and atomic types of molecular conformation,as the data descriptors,are applied as the network inputs to predict the interaction energy in the system.The neural network is trained with the hierarchically generated conformations data set.The complex tensor hidden layers are simplified and trained in the optimization process.The predicted results of different molecular sys tems indica te that deep t ensor neural net work is capable to predic t the interaction energy with 1 kcal/mol of the mean absolute error in a relatively short time.The prediction highly improves the efficiency of interaction energy calculation.The whole proposed framework provides new insights to introducing deep learning technology into the interaction energy calculation.展开更多
:20111287 Bai Xiaoyong(State Key Laboratory of Environmental Geochemistry,Institute of Geochemistry,CAS,Guiyang 550002,China);Wang Shijie Constrains of Lithological Background of Carbonate Rock on Spatio-Temporal Evol...:20111287 Bai Xiaoyong(State Key Laboratory of Environmental Geochemistry,Institute of Geochemistry,CAS,Guiyang 550002,China);Wang Shijie Constrains of Lithological Background of Carbonate Rock on Spatio-Temporal Evolution of Karst Rocky Desertification Land(Earth Science,ISSN1000-2383,CN42-1233/P,35(4),2010,p.691-696,4 illus.,2 tables,17 refs.)Key words:rock desertification,carbonate rocks,Guizhou Province In order to study the effect of lithological background of carbonate rock on spatio-temporal evolution of karst rocky desertification(RD)land,1∶100 000 scale digital RD distribution maps of Guizhou in 1986,1995 and 2000 were obtained by RS,GIS and GPS(3S)technology and user-computer interactive interpreting method from Landsat展开更多
基金This work was supported by the National Natural Science Foundation of China(No.21933010 to Guo-hui Li).
文摘The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction energy based on quantum mechanics can not be merged into molecular dynamic simulation for a long time scale.A deep learning framework,deep tensor neural network,is applied to predict the interaction energy of three organic related systems within the quantum mechanics level of accuracy.The geometric structure and atomic types of molecular conformation,as the data descriptors,are applied as the network inputs to predict the interaction energy in the system.The neural network is trained with the hierarchically generated conformations data set.The complex tensor hidden layers are simplified and trained in the optimization process.The predicted results of different molecular sys tems indica te that deep t ensor neural net work is capable to predic t the interaction energy with 1 kcal/mol of the mean absolute error in a relatively short time.The prediction highly improves the efficiency of interaction energy calculation.The whole proposed framework provides new insights to introducing deep learning technology into the interaction energy calculation.
文摘:20111287 Bai Xiaoyong(State Key Laboratory of Environmental Geochemistry,Institute of Geochemistry,CAS,Guiyang 550002,China);Wang Shijie Constrains of Lithological Background of Carbonate Rock on Spatio-Temporal Evolution of Karst Rocky Desertification Land(Earth Science,ISSN1000-2383,CN42-1233/P,35(4),2010,p.691-696,4 illus.,2 tables,17 refs.)Key words:rock desertification,carbonate rocks,Guizhou Province In order to study the effect of lithological background of carbonate rock on spatio-temporal evolution of karst rocky desertification(RD)land,1∶100 000 scale digital RD distribution maps of Guizhou in 1986,1995 and 2000 were obtained by RS,GIS and GPS(3S)technology and user-computer interactive interpreting method from Landsat
