Simulated annealing and neural networks as alternative methods for nonlinear constrained optimization

Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Volumn 381, Issue 1, 1996, Pages 152-156

  Carlson, P ^a   Danielsson, M ^a   Dejardin, M ^b   Jon And, K ^a   Sjolin J ^a  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b DIF   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONSTRAINT THEORY; CONVERGENCE OF NUMERICAL METHODS; CURVE FITTING; ELEMENTARY PARTICLES; ESTIMATION; KINEMATICS; MONTE CARLO METHODS; NEURAL NETWORKS; SIMULATED ANNEALING;

CONSTRAINED FITS CONVERGENCE; GEOMETRICAL CONSTRAINTS; KINEMATICAL CONSTRAINTS; NONLINEAR CONSTRAINED OPTIMIZATION;

HIGH ENERGY PHYSICS;

EID: 0030264358     PISSN: 01689002     EISSN: None     Source Type: Journal    
DOI: 10.1016/0168-9002(96)00737-1     Document Type: Article

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