NOVEL GA-BASED DNN ARCHITECTURE FOR IDENTIFYING THE FAILURE MODE WITH HIGH ACCURACY AND ANALYZING ITS EFFECTS ON THE SYSTEM СтатьяRezaeian N., Gurina R., Saltykova O.A., Hezla L., Nohurov M., Kashyzadeh K.R.APPLIED SCIENCES-BASEL. Том 14. 2024.
ENHANCED AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL FOR ANOMALY DETECTION IN POWER PLANT OPERATIONS СтатьяFahmi A.TWK., Kashyzadeh K.R., Ghorbani S.International Journal of Engineering. Том 37. 2024. С. 1691-1699
ADVANCEMENTS IN GAS TURBINE FAULT DETECTION: A MACHINE LEARNING APPROACH BASED ON THE TEMPORAL CONVOLUTIONAL NETWORK-AUTOENCODER MODEL СтатьяFahmi A.WK., Kashyzadeh K.R., Ghorbani S.APPLIED SCIENCES-BASEL. Том 14. 2024.
FAULT DETECTION IN THE GAS TURBINE OF THE KIRKUK POWER PLANT: AN ANOMALY DETECTION APPROACH USING DLSTM-AUTOENCODER СтатьяFahmi A.WK., Kashyzadeh K.R., Ghorbani S.Engineering Failure Analysis. Том 160. 2024.