American Institute of Physics Downloaded / American Institute of Physics / Oklahoma State University / /
IndustryTerm
minimum energy / gradient-based optimization algorithm / backpropagation42 training algorithm / chemical system / potential-energy hypersurfaces / chemical experiments / neural networks / potential-energy surfaces / bond dissociation gas-phase reaction / vinyl bromide2 systems / vibrational kinetic energy corresponding / median network / rotational energy / relative translational energy / moiety energy / model potential-energy hypersurface / typical potential-energy hypersurface / constant translational energy / energy / potential-energy hypersurface / multilayer network / zero-point energy / time interval algorithm / potential energy / improved neural network / eV standard energy deviation / initio potential energy surface / triplet energy states / force fields using feedforward neural networks / potential-energy surface / gas-phase chemical reactions / larger systems / regularization algorithm / energy lies / /
MarketIndex
set 470 / /
Organization
American Institute of Physics Downloaded / American Institute of Physics / National Science Foundation / Division of Civil / Mechanical / and Manufacturing Innovation / Oklahoma State University / Central Processing Unit / /
Person
T. Carrington / Jr. / D. E. Rumelhart / G. Wang / S. Manzhos / R. Dawes / A. H. Nelson / Jr. / R. J. Williams / T. J. Carrington / Jr. / G. E. Hinton / Jocelyn Harrison / /
Position
Program Director / Jr. Endowed Chair for additional financial support / representative / /
Product
NNs / /
ProgrammingLanguage
E / V / J / /
ProvinceOrState
New Jersey / Indiana / Oklahoma / Massachusetts / /
THE JOURNAL OF CHEMICAL PHYSICS 130, 134101 共2009兲 Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks A. Pukrittayakamee,1 M. Malshe,2 M. Hagan,1