000			01799cam a2200313 a 4500
003			EG-GiCUC
008			170604s2016 ua e f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.13.11.M.Sc.2016.An.A
100	0		_aAnwr Mohammed Albaghdadi
245	1	3	_aAn artificial neural network model for gas turbine performance prediction / _cAnwr Mohammed Albaghdadi ; Supervised M. G. Khalafallah , Abdelnaby Mohamed
246	1	5	_aالتنبؤ باداء التوربينات الغازية باستخدام نموذج الشبكات العصبيه الاصطناعيه
260			_aCairo : _bAnwr Mohammed Albaghdadi , _c2016
300			_a91 P. : _bplans ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Mechanical Power Engineering
520			_aThe present thesis introduces a study for the application of ANN modeling to investigate the performance prediction of a gas-turbine power-generation unit. A wide range of operating data (over two years) of a small gas turbine (20 MW) is used for training, investigating and evaluating the ANN model. ANN shows good predict ability results that would add an interesting advantage to the maintenance team efforts. Moreover, the model could be used as a guide for operators to estimate different failure possibilities that could happened to various parts of the gas turbine engine
530			_aIssued also as CD
653		4	_aArtificial neural network
653		4	_aGas turbine
653		4	_aPredict
700	0		_aAbdelnaby Mohamed Abdelfattah, _eSupervisor
700	0		_aMohamed Galal Eldin Khalafallah , _eSupervisor
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c61074 _d61074