Intelligence temperature prediction of molten steel in LF based on PSO combined with BP neural network

Kongzhi yu Juece/Control and Decision

Volumn 21, Issue 7, 2006, Pages

  Wang, An Na ^a   Tao, Zi Yu ^b   Jiang, Mao Fa ^b   Tian, Hui Xin ^a   Zhang, Li Na ^a  

^a NORTHEASTERN UNIVERSITY   (China)

^b NORTHEASTERN UNIVERSITY   (China)

Author keywords

BP neural network; LF refining temperature; Particle swarm optimization; Prediction of molten steel

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ARGON; BACKPROPAGATION; FURNACES; LADLES; MOLTEN MATERIALS; OPTIMIZATION; REFINING; STEEL; TEMPERATURE;

BACKPROPAGATION NEURAL NETWORK; CONVERGENCE CAPABILITY; INTELLIGENCE TEMPERATURE PREDICTION; LADLE FURNACE (LF); MOLTEN STEEL; PARTICLE SWARM OPTIMIZATION (PSO); REFINING TEMPERATURE;

NEURAL NETWORKS;

EID: 33748157443     PISSN: 10010920     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. Sun Y G, Wang D X, Tao B S, et al. An Intelligent Ladle Furnace Control System [J]. Metallurgical Industry Automation, 1999, (6): 9-12.
2. Wang X, Wang H, Wang W H. Theory and Application of Artificial Neural Network [M]. Shenyang: Publishing House of Northeastern University, 2002: 13-65.
3. Yan P F, Zhang C S. Artificial Neural Network and Simulation Evolution Computing [M]. Beijing: Publishing House of Tsinghua University, 2000.
4. Chow W S, Fang Y. A Recurrent Neural-network-based Real-time Learning Control Strategy Applying to Nonlinear Systems with Unknown Dynamics [J]. IEEE Trans on Neural Network, 1998, 45 (1): 151-161.
5. Shen W X, Chan C C, Lo E W C, et al. A New Battery Available Capacity Indicator for Electric Vehicles Using Neural Network [J]. J of Power Sources, 2002, 43 (6): 817-826.
6. Zhong L, Liu L S, Zou C M, et al. The Application of Neural Network in Life Time Prediction of Concrete [J]. J of Wuhan University of Technology, 2002, 17 (1): 79-81.
7. Kennedy J, Eberhart R C. Particle Swarm Optimization [A]. Proc IEEE Int Conf on Neural Networks [C]. Perth: IEEE Piscataway, 1995: 1942-1948.
8. Kannana S, Mary S, Slochanal R, et al. Application of Particle Swarm Optimization Technique and Its Variants to Generation Expansion Planning Problem [J]. Electric Power Systems Research, 2004, 70 (8): 203-210.
9. Yi D, Ge X R. An Improved PSO-based ANN with Simulated Annealing Technique [J]. Neurocomputing, 2005, 63 (11): 527-533.