الفهرس 
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Abstract
”In today’s climate of growing energy needs and increasing environmental concern, alternatives to the use of non-renewable and polluting fossil fuels have to be investigated. Most of the countries focus more on renewable energy, especially on wind energy resources due to global climate change. Wind energy is the only renewable energy technology currently ready to deliver on a significant scale. The selection of suitable geographic locations for wind farms can be a challenging task due to the various decision-makers involved in the process. In addition, selection criteria differ depending on the decision maker’s preferences. Decision-makers often face complicated decision problems with intangible and conflicting criteria. Numerous Multi-Criteria Decision Making (MCDM) methods have been proposed to handle the measurement of the priorities of conflicting tangible/intangible criteria and in turn, use them to choose the best alternative for a decision. Traditional decision-making methods would not achieve the proper ideal decisions. Due to environmental, natural, and socio-economic reasons. The decision-makers would have some misjudgments due to lack of experience, confusion, bias, various alternatives, and conflicting criteria. Geographical Information System (GIS) software is a powerful tool for enhancing spatial decisions. In this dissertation, a neutrosophic hybrid MCDM-GIS Framework is proposed to identify suitable areas for wind power development in the Sinai Peninsula, Egypt. The analysis of the area will be based on several evaluation and constraint criteria. Then, these areas can be assessed based on the preferences of wind power experts and administration authorities, while the MCDM method can be used to incorporate different opinions and reach a possible consensus. The MCDM technique to be implemented in this research; is the Analytical Network Process (ANP) with the bipolar neutrosophic numbers (BNN) to illustrate the values of attributes to accommodate the lack of decision information. Finally, the entropy Shannon method is used for choosing the potential alternative wind power plant sites, and using the Preference Ranking Organization Method for Enrichment Evaluations-II (PROMETHEE-II) and order preference by similarity to ideal solution (TOPSIS) to help decision-makers find the best possible alternative; and establishing the supremacy of one option over the other. The proposed BNN-ANP framework in a GIS environment was applied to determine the potential area for wind farm installation. The wind potential area of the study that was found to be suitable and not suitable for the installation of wind turbines is as follows: 2,509 km2 (4% of the study area) is the less suitable; 14,688 km2 (24% of the study area) is moderately suitable; 8,873 km2 (15% of the study area) is highly suitable, and 34,814 km2 (57% of the study area)viiis not suitable. After that, Extract the total area available for installable wind farm development under the ‘highly suitable’. This area has been divided into four alternatives ‘A,’, ‘B’, ‘C’, and ‘D’. Then, use the Shannon entropy method to evaluate the four alternatives in an objective method. After that, PROMETHEE-II and TOPSIS applied for ranking alternatives. The results of this ranking argue that alternative ‘D’ is the first-ranked alternative and the best choice; followed by alternative ‘B’; then alternative ‘A’; and alternative ‘C’ is the last-ranked alternative and the worst option. In the last step of the study, the effectiveness and advantages of the proposed framework are demonstrated through comparison with two methods Analytic Hierarchy Process (AHP) and Crisp ANP (CANP). It can be said from the observation that in both AHP and CANP, the competency points of all alternatives are much closed. More precisely, if the points are rounded up to three decimal places, the result is almost the same. But in the proposed framework, each alternative has a competency score, which leaves no confusion for the decision-maker to take the final decision.”