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Kramer, M. A. (1991). Nonlinear principal componenet analysis using autoassociative neural networks. AIChE Journal, 37, 233–243.
Scholz M., Fraunholz M., Selbig J. (2007) Nonlinear Principal Component Analysis: Neural Network Models and Applications in Principal Manifolds for Data Visualization and Dimension Reduction, pp. 44–67
Simani, S. (2005). Identification and fault diagnosis of a simulated model of an industrial gas turbine. IEEE Transactions on Industrial Informatics, 1, 202–216.
Guo Z., Uhrig R. E. (1992). Using genetic algorithms to select inputs for neural networks. In COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks. pp. 223–234
Nelles, O. (2001). Nonlinear System Identification. Berlin: Springer.
Oliveira, G. H. C., Campello, R. J. G. B., & Amaral, W. C. (1999). Fuzzy models within orthonormal basis function framework. In Fuzzy Systems Conference Proceedings, FUZZ-IEEE ’99. IEEE International, 2, 957–962.
Medeiros, A. V., Amaral W. C., Campello R. J. G. B. (2006). GA Optimization of OBF TS Fuzzy Models with Linear and non Linear Local Models. In 2006 Ninth Brazilian Symposium on Neural Networks (SBRN ’06). (pp. 66–71).
Campello R. J. G. B., Amaral W. C. (2002) Takagi-Sugeno fuzzy models within orthonormal basis function framework and their application to process control. In Proceedings of the 2002 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE’02. (pp. 1399–1404)
Machado J. B., Amaral W. C., Campello R. J. G. (2007). Design of OBF-TS Fuzzy models based on multiple clustering validity criteria. In 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007). (pp. 336–339)
Alci, M., & Asyali, M. H. (2009). Nonlinear system identification via Laguerre network based fuzzy systems. Fuzzy Sets and Systems., 160, 3518–3529.
Saravanamutto H. I. H., Rogers G. F. C., Cohen H. (1996). Gas Turbine Theory, (4th ed.).: Longman Group Limited
Walsh P. P., Fletcher P. (2004) Gas Turbine Performance. Blackwell Science Ltd.
Schobeiri M. (2005) Turbomachinery Flow Physics and Dynamic Performance. Verlag, Berlin, Heidelberg: Springer
Razak A. M. Y. (2007). Industrial Gas Turbines Performance and Operability. Woodhead Publishing Limited, CRC Press, LLC
Chui C. K. (1992). An Introduction to Wavelets. Academic Press Limited
Nelles, O. (1997). Orthonormal Basis Functions for Nonlinear System Identification with Local Linear Model Trees (LOLIMOT). IFAC Symposium on System Identification (SYSID) (pp. 667–672). Fukuoka, Japan: Kitakyushu.
Haglind, F. (2010). Variable geometry gas turbines for improving the part-load performance of marine combined cycles - gas turbine performance. Energy, 31, 467–476.
Coverse G. L. (1984). Extended Parametric Representation of Compressor Fans and Turbines Volume 2: Part user’s Manual (Parametric Turbine). NASA-CR-174646
Seborg D. E., Edgar T. F., Mellichamp D. A. (2003). Process Dynamics and Control. John Wiley and Sons
Mikles J., Fikar M. (2007). Process Modelling Identification and Control. Verlag: Springer
Srinivasarao M., Patwardhan S. C., Gudi R. D. (2006). From data to nonlinear predictive control. 1. Identification of multivariable nonlinear state observers. Industrial and Engineering Chemistry Research.
Dincer I., Rosen M. A. (2007). Exergy: Energy, Environment, and Sustainable Development. Elsevier Ltd
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Lemma, T.A. (2018). Intelligent Fault Detection and Diagnostics. In: A Hybrid Approach for Power Plant Fault Diagnostics. Studies in Computational Intelligence, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-319-71871-2_5
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