طبقه بندی و پیش بینی متغیرهای پورت با استفاده از شبکه های بیزی / Classification and prediction of port variables using Bayesian Networks

طبقه بندی و پیش بینی متغیرهای پورت با استفاده از شبکه های بیزی Classification and prediction of port variables using Bayesian Networks

  • نوع فایل : کتاب
  • زبان : انگلیسی
  • ناشر : Elsevier
  • چاپ و سال / کشور: 2018

توضیحات

رشته های مرتبط مهندسی کامپیوتر، فناوری اطلاعات
گرایش های مرتبط هوش مصنوعی، شبکه های کامپیوتری
مجله سیاست حمل و نقل – Transport Policy
دانشگاه Civil Engineering Department – Transports – Polythecnic University of Madrid – Spain
شناسه دیجیتال – doi http://dx.doi.org/10.1016/j.tranpol.2017.07.013
منتشر شده در نشریه الزویر

Description

1. Introduction Sustainable development is beeing applied emergently by transport authorities and in other activity sectors and industries all over the World. It is proponted by iniciatives which include environmental variables and social responsibility in strategic management of companies (Doerr, 2011). This is port case. Port sustainability is rooted in the proposals of the GRI (Global Reporting Initiative, 2000) and it preserves the four main ideas or dimensions which knock into shape sustainable development – institutional, economic, environmental and social dimensions- It is considered that sustainable management of a company or organism has as main target equilibrate keeping of its function and activity for a long time. So, it is necessary looking for an equilibrate development of economic, social, environmental and institutional dimensions (Serrano, 2015). This concept is beeing applied emergently by transport authorities and in other activity sectors and industries all over the World. It is proponted by iniciatives which include environmental variables and social responsibility in strategic management of companies (Doerr, 2011). This is port case. Port sustainability is rooted in the proposals of the GRI (Global Reporting Initiative, 2000) and it preserves the four main ideas or dimensions which knock into shape sustainable development – institutional, economic, environmental and social dimensions- (Fig. 1). It is considered that sustainable management of a company or organism has as main target equilibrate keeping of its function and activity for a long time. So, it is necessary looking for an equilibrate development of economic, social, environmental and institutional dimensions (Serrano, 2015). In this context, maritime transport requires an especial attention, because it transports over 80% foreign trade (tonelates-kilometres) (Sanchez et al., 2015). So, sustainable management must be understood in port sector as “management which allows containers traffic, solid and liquid granels, general goods and number of passenger grow up at the same time that energy and natural resources purchase, rubbish volume and negative impacts over social systems and ecosystems decreases in port influence areas” (Crespo Soler et al., 2005). However, one of the principal challenges to integrate sustainable criterias in management model and port development is broken out present inertia which considers economic factor as unique development variable. It is necessary that environmental and social variables gain importance to make port development travels to sustainability (Grupo de Trabajo 23, 2004). Spanish State Ports and Merchant Navy Law includes sustainability as one of the principles which must regulate planning model and port management. Article 55.4 foresees company planning of each Port Authority must be gone with a sustainability report-it is considered as an analysis and diagnostic tool-. This report use a methodology which is based on GRI’s one, but includes specific quality indicators and must be approved by Spanish State Ports and Port Authorities. Redaction of these reports is an important effort to integrate information about Port Authority behavior and information about its environmental, economic and social performance. However, this report does not determine Port Authority behavior, it only describes results using performance quality indicators (Crespo Soler et al., 2007).
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