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003			EG-GiCUC
005			20250223032921.0
008			220216s2021 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.20.02.M.Sc.2021.Ra.L
100	0		_aRawaa Hesham Abdelhay Elbidweihy
245	1	0	_aLife cycle assessment of renewable energy in Egypt by 2035 using dynamic bayesian networks / _cRawaa Hesham Abdelhay Elbidweihy ; Supervised Ihab A. Elkhodary , Hisham M. Abdelsalam
246	1	5	_aتقييم دورة حياة الطاقة المتجددة فى مصر بحلول عام 2035 باستخدام شبكة بايزى الديناميكيه
260			_aCairo : _bRawaa Hesham Abdelhay Elbidweihy , _c2021
300			_a154 P . : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Operations Research and Decision Support
520			_aIn an era where machines run and shape our world, the need for a stable, non-ending source of energy emerges. In this study, the focus is on the solar energy in Egypt as a renewable source, the most important factors that could affect the solar energy{u2019}s market share throughout its life cycle production are analyzed and filtered, the relationships between them are derived before structuring a Bayesian network. Also, forecasted models are built for multiple factors to predict their future values in Egypt by 2035, based on historical data and patterns; to be used as the nodes{u2019} states in the network. 37 factors are found to have a possible impact on the use of solar energy. They are reduced to 12 factors that are chosen to be the most effective to the solar energy{u2019}s life cycle in Egypt, based on surveying experts and data analysis; some of the factors are found to be recurring in multiple stages. The states of the factors in the constructed Bayesian network are indicated based on the followed data distribution type for each factor, and using either the Z-distribution approach or the Cheby shev{u2019}s inequality theorem Later on, the individual and the conditional probabilities of the states of each factor in the Bayesian network are derived either from the collected and scrapped historical data or from estimations and past studies. Results show that we can use the constructed model for scenario and decision analysis concerning forecasting the total percentage of the market share of the solar energy in Egypt and using it as a stable renewable source for generating any type of energy needed
530			_aIssued also as CD
650		0	_aBayesian analysis
653		4	_aDynamic bayesian networks
653		4	_aRenewable energy
653		4	_aThe solar energy
700	0		_aHisham Mohamed Abdelsalam , _eSupervising
700	0		_aIhab Ahmed Elkhodary , _eSupervising
856			_uhttp://172.23.153.220/th.pdf
905			_aAmira _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c84243 _d84243