A comparison of neural networks architectures for particle size distribution estimation in wet grinding circuits

ISA TECH/EXPO Technology Update Conference Proceedings

Volumn 413 I, Issue , 2001, Pages 85-93

  Sbarbaro, D ^a   Barriga, J ^a   Valenzuela, H ^a   Cortes, G ^a   Mujica, L ^a   Perez, N ^a  

^a UNIVERSITY OF CONCEPCIÓN   (Chile)

Author keywords

Neural networks; Particle size distribution; Soft sensors; Wet grinding circuit

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; MATHEMATICAL MODELS; NOISE ABATEMENT; PARAMETER ESTIMATION; PARTICLE SIZE ANALYSIS; SENSORS;

AUTOASSOCIATIVE NETWORK; LEVENBERG MARQUARDT ALGORITHM; NEURAL NETWORKS ARCHITECTURES; SOFTSENSORS; STANDARD FEEDFORWARD NETWORK; WET GRINDING CIRCUITS;

FEEDFORWARD NEURAL NETWORKS;

EID: 0035173462     PISSN: 10540032     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Neural net-based softsensor for dynamic particle size estimation in grinding circuits
2. Particle size distribution soft-sensor for a grinding circuit
3. Gauss-newton approximation to bayesian regularization
4. Autoassociative neural networks
5. A new method for identifying orders of input-output models for nonlinear dynamic systems