Items where Author is "Sarwar, U."

Soomro, A.A. and Mokhtar, A.A. and Kurnia, J.C. and Lashari, N. and Sarwar, U. and Jameel, S.M. and Inayat, M. and Oladosu, T.L. (2022) A review on Bayesian modeling approach to quantify failure risk assessment of oil and gas pipelines due to corrosion. International Journal of Pressure Vessels and Piping, 200.

Muhammad, M.B. and Sarwar, U. and Tahan, M. and Karim, Z.A.A. (2018) Intelligent fault diagnostic model for rotating machinery. IEEE International Conference on Industrial Engineering and Engineering Management, 2017-D. pp. 1858-1862.

Muhammad, M.B and Sarwar, U. and Tahan, M.R. and Abdul Karim, Z.A. (2016) Fault diagnostic model for rotating machinery based on principal component analysis and neural network. ARPN Journal of Engineering and Applied Sciences, 11 (24). pp. 14327-14331.

Muhammad, M.B and Sarwar, U. and Tahan, M.R. and Abdul Karim, Z.A. (2016) Fault diagnostic model for rotating machinery based on principal component analysis and neural network. ARPN Journal of Engineering and Applied Sciences, 11 (24). pp. 14327-14331.

Tahan, M. and Sarwar, U. and Muhammad, M. and Abdul Karim, Z.A. (2016) Modeling and sensitivity analysis of a multi-nets anns model for real-time performance-based condition monitoring of an industrial gas turbine engine. ARPN Journal of Engineering and Applied Sciences, 11 (24). pp. 14269-14274.

Tahan, M. and Sarwar, U. and Muhammad, M. and Abdul Karim, Z.A. (2016) Modeling and sensitivity analysis of a multi-nets anns model for real-time performance-based condition monitoring of an industrial gas turbine engine. ARPN Journal of Engineering and Applied Sciences, 11 (24). pp. 14269-14274.

Sarwar, U. and Muhammad, M.B. and Abdul Karim, Z.A. (2014) Time series method for machine performance prediction using condition monitoring data. In: UNSPECIFIED.