مقاله انگلیسی رایگان در مورد روش تصمیم گیری گروهی بر اساس یک فرآیند تحلیل شبکه – IEEE 2017

مقاله انگلیسی رایگان در مورد روش تصمیم گیری گروهی بر اساس یک فرآیند تحلیل شبکه – IEEE 2017

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۷
تعداد صفحات مقاله انگلیسی ۵ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه IEEE
نوع مقاله ISI
عنوان انگلیسی مقاله A Bayesian-ANP-Based Expert Group Decision-Making Method to Evaluate the Location of Military Port
ترجمه عنوان مقاله روش تصمیم گیری گروهی تخصصی بر اساس یک فرآیند تحلیل شبکه (ANP) بیزین به منظور ارزیابی مکان بندر نظامی
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مدیریت، فناوری اطلاعات
گرایش های مرتبط مدیریت فناوری اطلاعات
مجله سومین کنفرانس بین المللی کامپیوتر و ارتباطات – ۳rd IEEE International Conference on Computer and Communications
دانشگاه Institute of Naval Logistics – Tianjin – China
کلمات کلیدی موقعیت بندر نظامی؛ سیستم ارزیابی ANP؛ تئوری ائتلاف بیزی؛ روش تصمیم گیری گروه متخصص
کلمات کلیدی انگلیسی location of military port; ANP evaluation system; bayesian fusion theory; expert group decision-making method
شناسه دیجیتال – doi
https://doi.org/10.1109/CompComm.2017.8322694
کد محصول E8677
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بخشی از متن مقاله:
I. INTRODUCTION

The location of military engineering(LME) is an important aspect of battlefield environment construction in the future information condition. A success of LME, directly related to the realization of the national strategy, the rational use of national resources and the effective use of defense funds, operation command comprehensive coordination, the optimized allocation of battlefield target , etc. In the case of the construction of a large integrated strategic homeport, it is indispensable to support a growing fleet and the country’s frontier maritime strategy. In existing port or the port group, to chose the basic conditions are relatively good, and had the potential to extend the facility for key construction and make it to its homeport, not only conform to the requirements of the future naval strategy and berthing ship’s security requirements, but also can save construction investment, the navy can make full use of the facility results on the basis of the existing building, make more power for port shore facilities maintenance, update and supplement. In other words, a suitable location of the military port˄LMP˅ is of great significance to improve the strategic value, to give full play of security efficiency and to improve the military economic benefits. At present, there are a lot of existing location assessment methods, Xiao Ding et al. apply the method of entropy weight and ideal point method to select a site for civil port [1]. Huang Mingsheng and Taih-Cherng Lirn adopt AHP method to decided the weights of site selection [2] [3]; Liu Linhu et al. using principal component analysis to select candidate military logistics base, on the basis of the maximum coverage model are used to determine a location decision [4]. The mufti-objective decision model of military engineering location is constructed by Weng Dongfeng [5]. Halpern proposed a two-level standard plane model for the actual problem of site selection for the first time[6]. Ayfer and Ergin has applied ELECTRE method to the site selection of container ports [7]. It is required that when the above methods in constructing a model of the whole evaluation system has a complete cognitive structure, and the relationship between the accurate model covers the elements of information is less, but through the study found that the construction of port planning and site selection evaluation indicator is broad, the relevance between the indicators are hidden, the elements in the system is not absolutely independent, but mutual influence and interdependence. In order to make the result of LMP more reasonable and credible, this paper proposes a Bayesian-ANP-based assessment method, which is fused expert group of judgment through comprehensive consideration all experts preference indicator correlation of evaluation, and optimize the process of the construction of the ANP model, overcome the subjective arbitrariness of independent evaluation, improve the reliability of the ANP model.

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