000			01781cam a2200313 a 4500
003			EG-GiCUC
008			140108s2013 ua dh f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.13.05.M.Sc.2013.So.D
100	0		_aSohaib Mundher Hussein Alukashy
245	1	0	_aDeveloping an rtificial neural network to predict the effect of sulfate attack on the concrete structures / _cSohaib Mundher Hussein Alukashy ; Supervised Osama A. Hodhod , Mostafa A. Abdeen
246	1	5	_aتطوير شبكة عصبية اصطناعية للتنبؤ بتأثير مهاجمة الكبريتات للمنشآت الخرسانية
260			_aCairo : _bSohaib Mundher Hussein Alukashy , _c2013
300			_a84 P. : _bcharts , facsimiles ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Civil Engineering
520			_aIn this study, an artificail neural network (ANN) is developed to be used in prediciting the reduction incompressive strength of concrete exposed to sulfate bearing environments. A total of 214 cases are gathered from pertinent literature. The data used in developing the artificial neural network model are arranged in a format of nine inputs which are: cement type, cement content,water to cement ratio, fine and coarse aggregate contents, mineral admixture type and content, type and concentration of sulfate salt, and exposure time
530			_aIssued also as CD
653		4	_aANN
653		4	_aSoft computing
653		4	_aSulfate attack
700	0		_aMostafa Ahmed Abdeen , _eSupervisor
700	0		_aOsama A. Hodhod , _eSupervisor
905			_aAml _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c44782 _d44782