Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databases

Journal of Chemical Physics

Volumn 132, Issue 20, 2010, Pages

  Malshe, M ^a   Raff, L M ^b   Hagan, M ^a   Bukkapatnam, S ^a   Komanduri, R ^a  

^a Oklahoma State University   (United States)

^b OKLAHOMA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AB INITIO; AB-INITIO ELECTRONIC STRUCTURE CALCULATIONS; BASIS SETS; BODY ANGLE; BOND RUPTURE; BOND TYPE; CHEMICAL BONDINGS; CIS-TRANS; COMPUTATIONAL EFFORT; DENSITY FUNCTIONALS; DIHEDRAL ANGLES; DISSOCIATION REACTIONS; ELECTRONIC STRUCTURE CALCULATIONS; ERROR MINIMIZATION; FITTING ACCURACY; FITTING ERROR; HIGH ENERGY; INPUT VECTOR; INTER-ATOMIC DISTANCES; INTERPARTICLE DISTANCES; LEVENBERG-MARQUARDT; MACHINING CONDITIONS; MOLECULAR CONFIGURATIONS; OPTIMUM VALUE; PLANAR GEOMETRIES; RATE OF CHANGE; RMS ERRORS; VINYL BROMIDES; Z MATRIX;

CHEMICAL BONDS; DATABASE SYSTEMS; ELECTRONIC PROPERTIES; ELECTRONIC STRUCTURE; ISOMERIZATION; MACHINERY; NEURAL NETWORKS; OPTIMIZATION; POTENTIAL ENERGY; SILICON; VECTORS;

CHEMICAL ELEMENTS;

EID: 77953036659     PISSN: 00219606     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.3431624     Document Type: Article

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