Permeability prediction model for imperial smelting furnace based on improved case-based reasoning

Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

Volumn , Issue , 2008, Pages 1967-1970

  Yang, Chunhua ^a   Zhu, Hongqiu ^a   Gui, Weihua ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Adaptive PSO; Imperial Smelting Furnace; Improved CBR; Permeability index prediction

Indexed keywords

ADAPTIVE ALGORITHMS; BITS; CAPILLARITY; FORECASTING; FURNACES; INDUSTRIAL ENGINEERING; INTELLIGENT CONTROL; LEARNING SYSTEMS; LIQUIDS; MATHEMATICAL MODELS; METAL REFINERIES; METALLURGICAL FURNACES; OPTIMIZATION; PARTICLE SWARM OPTIMIZATION (PSO); SMELTING; STANDARDS;

ADAPTIVE PARTICLE SWARM OPTIMIZATION; ADAPTIVE PSO; CASE BASED; CASE RETRIEVAL; CONTROL AND AUTOMATION; FIELD PRODUCTION DATA; IMPERIAL SMELTING FURNACE; IMPERIAL SMELTING FURNACES; IMPROVED CBR; INTELLIGENT PREDICTION; K-NEAREST NEIGHBOR ALGORITHM; MATHEMATICAL MODELLING; MODEL ACCURACY; NEAREST NEIGHBORS; PERMEABILITY INDEX; PERMEABILITY INDEX PREDICTION; PREDICTION MODELING; PRODUCTION DATA; RETRIEVAL ACCURACY; SIMILARITY MEASURING; SMELTING PROCESS; WEIGHTED AVERAGING; WEIGHTED VECTOR;

CASE BASED REASONING;

EID: 52149100376     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WCICA.2008.4593226     Document Type: Conference Paper

References (11)

1. Editorial Committee of Metallurgy of Lead and Zinc. Metallurgy of Lead and Zinc. Beijing: Science Press, 2003.
2. A. Sunny Ochi-Okorie, Disease diagnosis validation in TROPIX using CBR, Artificial Intelligence in Medicine, 1998, 12(1): 43-60
3. Amjad Waheed, Hojjat Adeli. Case-based reasoning in steel bridge engineering, Knowledge-Based Systems, 2005, 18(1): 37-46
4. E.B Reategui, J.A Campbell,B.F Leao. Combining a neural network with case-based reasoning in a diagnostic system, Artificial Intelligence in Medicine, 1997, 9(1): 5-27
5. S. Wesley Changchien, Ming-Chin Lin. Design and implementation of a casebased reasoning system for marketing plans, Expert Systems with Applications, 2005, 28(1): 43-53
6. C. M. Vong, T. P. Leung, P. K. Wong. Case-based reasoning and adaptation in hydraulic production machine design, Engineering Applications of Artificial Intelligence, 2002, 15(6): 567-585
7. C., K. Kwong; Smith, G.F.; W., S. Lau, Application of Case Based Reasoning in Injection Moulding, Journal of Materials Processing Technology, 1997, 63(1-3): 463-467
8. J. Kennedy, R.C. Eberhart, Particle swarm optimization, Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, 1995, 1942-1948.
9. R.C. Eberhart, J. Kennedy, A new optimizer using particle swarm theory. Proceeding of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan (1995) 39-43.
10. Krink T, Vesterstrom JS, Riget J. Particle swarm optimization with spatial particle extension. Proceedings of IEEE Congress on Evolutionary Computation, Honolulu, Hawaii, USA, 2002, 1474-1497
11. ZHANG Li-ping, YU Huan-jun, CHEN De-zhao, HU Shang-xu, Analysis and Improvement of Particle Swarm Optimization Algorithm, Information and Control, 2004,33(5): 515-516 (in chinese)