Journal of Engineering and Applied Sciences

Year: 2018
Volume: 13
Issue: 3
Page No. 607 - 618

Intelligent Systems for Equipment Health Management and Optimum Control in Phosphate Production

Authors : Batyrbek Suleimenov, Laura Sugurova, Aituar Suleimenov and Alibek Suleimenov

References

Abas, A.R., 2013. Adaptive competitive learning neural networks. Egypt. Inf. J., 14: 183-194.
CrossRef  |  

Aitbayevich, S.B., S.L. Alkhaidarovna and S.A. Batyrbekovich, 2015. Intelligent and hybrid systems of process control: Theory, methods, applications. Mediterr. J. Soc. Sci., 6: 627-642.
CrossRef  |  Direct Link  |  

Bobillo, F. and U. Straccia, 2008. Fuzzy DL: An expressive fuzzy description logic reasoner. Proceedings of the IEEE International Conference on Fuzzy Systems and IEEE World Congress on Computational Intelligence (FUZZ-IEEE’08), June 1-6, 2008, IEEE, Hong Kong, China, ISBN:978-1-4244-1818-3, pp: 923-930.

Fazilat, H., S. Akhlaghi, M.E. Shiri and A. Sharif, 2012. Predicting thermal degradation kinetics of nylon6/feather keratin blends using artificial intelligence techniques. Polymer, 53: 2255-2264.
CrossRef  |  

Hodge, V.J., S. O’Keefe and J. Austin, 2016. Hadoop neural network for parallel and distributed feature selection. Neural Netw., 78: 24-35.
PubMed  |  Direct Link  |  

Kalman, R.E., P.L. Falb and M.A. Arbib, 1969. Topics in Mathematical System Theory. McGraw-Hill, New York, USA., Pages: 358.

Kalogirou, S.A., 2003. Artificial intelligence for the modeling and control of combustion processes: a review. Prog. Energy Combustion Sci., 29: 515-566.
CrossRef  |  

Khatibi, R., M.A. Ghorbani, M.H. Kashani and O. Kisi, 2011. Comparison of three artificial intelligence techniques for discharge routing. J. hydrol., 403: 201-212.
CrossRef  |  

Leonenkov, A.V., 2003. Fuzzy Modeling in the МАТLAB and Fuzz-Tech Environments. BHV-Petersburg Publisher, Saint Petersburg, Russia, Pages: 726.

Mayrhauser, A.V., R. France, M. Scheetz and E. Dahlman, 2000. Generating test-cases from an object-oriented model with an artifical-intelligence planning system. IEEE. Trans. Reliab., 49: 26-36.
CrossRef  |  Direct Link  |  

Mukhanov, B.K., A. Suleimenov, W. Wojcik and K. Gromaszek, 2012. Development of an optimal control system for smelting process in the molten-pool. Electrotechnical Rev., 88: 366-368.

Rutkovskiy, L., 2010. Methods and Technologies of Artificial Intelligence. Moscow Publisher, Moscow, Russia, Pages: 354.

Saxena, A.K., S. Sharma and V.K. Chaurasiya, 2015. Neural network based human age-group estimation in curvelet domain. Procedia Comput. Sci., 54: 781-789.
CrossRef  |  

Suleimenov, B., L. Sugurova, N. Turynbetov and A. Suleimenov, 2014. Concept of developing an intelligent system for control and operational diagnostics of technological equipment condition. Inf. Control. Meas. Econ. Environ. Prot., 4: 27-32.
Direct Link  |  

Suleimenov, B.A. and D.Z. Hammetov, 2011. The development of MES technology for agglomerating branch of NDPP. Eng. J. Autom. Her., 33: 10-13.

Suleimenov, B.A., 2009. Intelligent and Hybrid Control Systems of Technological Processes. Almaty Publisher, Almaty, Kazakhstan, Pages: 304.

Suleimenov, B.A., G.M. Mutanov and A.B. Suleymanov, 2012. Intelligent Control Systems: Theory, Methods, Tools. Kazakh-American University, Almaty, Kazakhstan, Pages: 223.

Swedrowski, L., K. Duzinkiewicz, M. Grochowski and T. Rutkowski, 2014. Use of neural networks in diagnostics of rolling-element bearing of the induction motor. Key Eng. Mater., 588: 333-342.
Direct Link  |  

Szandała, T., 2015. Comparison of different learning algorithms for pattern recognition with hopfield's neural network. Procedia Comput. Sci., 71: 68-75.
CrossRef  |  

Uraikul, V., C.W. Chan and P. Tontiwachwuthikul, 2007. Artificial intelligence for monitoring and supervisory control of process systems. Eng. Appl. Artif. Intell., 20: 115-131.
CrossRef  |  

Vijayaraghavan, V., A. Garg, C.H. Wong and K. Tai, 2014. Estimation of mechanical properties of nanomaterials using artificial intelligence methods. Appl. Phys. A., 116: 1099-1107.
Direct Link  |  

Wang, J.H., H.Y. Wang, Y.L. Chen and C.M. Liu, 2015. A constructive algorithm for unsupervised learning with incremental neural network. J. Applied Res. Technol., 13: 188-196.
CrossRef  |  Direct Link  |  

Wojcik, W., B. Suleimenov, G. Shadrin, M. Shadrin and D. Porubov, 2014. Optimal control system of diesel automotive engineering by example of open pit motor transport. Inf. Technol. Autom. Meas. Economy Environ. Prot., 1: 14-17.

Yang, Z., H. Si and H. Zhao, 2013. Condition monitoring and diagnostics for complex system using neural networks. J. Appl. Sci., 13: 2710-2714.
CrossRef  |  Direct Link  |  

Zadeh, L.A., 1975. The concept of a linguistic variable and its application to approximate reasoning-II. Inf. Sci., 8: 301-357.
CrossRef  |  

Zadeh, L.A., 2008. Is there a need for fuzzy logic?. Inf. Sci., 178: 2751-2779.
Direct Link  |  

Zaychenko, Y.P., 2008. Models and Methods in Intelligent Systems: Study Guide for Students of Higher Educational Institutions. SLOVO Publishing House, Moscow, Russia, Pages: 344.

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