Computer modelling of mineral processing equipment using fuzzy mathematics

Minerals Engineering

Volumn 9, Issue 2, 1996, Pages 183-194

  Karr, C L ^a   Weck, B ^b  

^a UNIVERSITY OF ALABAMA   (United States)

^b NONE

Author keywords

Artificial intelligence; Grinding; Hydrocyclones; Modelling

Indexed keywords

COMPUTATIONAL LINGUISTICS; COMPUTER SIMULATION; GENETIC ALGORITHMS; GRINDING (COMMINUTION); MATHEMATICAL MODELS; MEMBERSHIP FUNCTIONS; MINERALS; PROCESSING;

FUZZY LINGUISTIC MODELS; FUZZY MATHEMATICS; GRINDING CIRCUIT; HYDROCYCLONES; MINERAL PROCESSING EQUIPMENT;

FUZZY SETS;

EID: 0030084179     PISSN: 08926875     EISSN: None     Source Type: Journal    
DOI: 10.1016/0892-6875(96)00003-9     Document Type: Article

References (19)

1. Cox, B.J., Object Oriented Programming. Reading, MA: Addison-Wesley, (1987).
2. Evans, G.W., Karwowski, W. & Wilhelm, M.R., (Eds.) Applications of Fuzzy Set Methodologies in Industrial Engineering. New York, NY: Elsevier Science Publishing Company, (1989).
3. Stock, M., AI in Process Control: New York, NY: McGraw-Hill Book Company, (1989).
4. Parsaye, K. & Chignell, M., Intelligent Database Tools & Applications, New York, NY: John Wiley & Sons, (1993).
5. Kelly, E.G. & Spottiswood, D.J., Introduction to Mineral Processing, New York, NY: John Wiley & Sons, (1982).
6. Karr, C.L., Yeager, D. & Stanley, D.A., Tuning empirical computer models using genetic algorithms: Proceedings of the Society of Computer Simulation Summer Conference, 236-241 (1994).
7. Karr, C.L., Strategy for adaptive process control for a column flotation unit: Proceedings of the Fifth Workshop on Neural Networks, SPIE 2204, 95-100 (1993).
8. Karr, C.L., Optimization of a computer model of a grinding process using genetic algorithms: In H. El-Shall, B. Moudgil, and R. Weigel, Beneficiation of Phosphate: Theory and Practice. Littleton, CO: Society for Mining, Metallurgy, and Exploration, 339-345 (1993).
9. Bickel, P.J., On some analogues to linear combination of order statistics in the linear model, Ann. Stat., 1, 597-616 (1973).
10. Andrews, D.F., A robust method for multiple linear regression, Technometrics, 16, 523-531 (1974).
11. Rousseeuw, P.J., Least median of squares regression: Journal of the American Statistical Association, 79, 871-880 (1984).
12. Wasserman, P.D., Neural computing, New York, NY: Van Nostrand Reinhold, (1989).
13. Zadeh, L.A., Outline of a new approach to the analysis of complex systems and decision processes: IEEE Transactions on Systems, Man, and Cybernetics, SMC-3(1), 28-44 (1975).
14. Karr, C.L., Genetic algorithms for fuzzy controllers: AI Expert, 6 (2), 26-33 (1991).
15. Goldberg, D.E., Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison Wesley, (1989).
16. Mehta, R.K., Kumar, K.K. & Schultz, C. W. (1992). Multiple objective optimization of a coal grinding process via simple genetic algorithm. Preprint number 92-108, Society for Mining, Metallurgy, and Exploration, Inc., Littleton, CO: (1992).
17. Wills, B.A., Mineral Processing Technology. Pergamon Press, Oxford, (1992).
18. Plitt, L.R., A mathematical model of the hydrocyclone classifier. CIM Bulletin, 69: 114-123, (1976).
19. Karr, C.L., Stanley, D. A. & Scheiner, B. J., A Genetic Algorithm Applied to Least Squares Curve Fitting, Report of Investigations number 9339, Washington DC: U.S. Department of the Interior, Bureau of Mines, (1991).