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Raspe – Risk Advisory Smart System For Pipeline Projects In Egypt

Authors: Nael Y. Zabel; Maged E. Georgy; Moheeb E. Ibrahim;

Raspe – Risk Advisory Smart System For Pipeline Projects In Egypt

Abstract

{"references": ["N. Y. Zabel, M. E. Georgy, and M. E. Ibrahim, \"Developing a Dynamic\nRisk Map (DRM) for Pipeline Construction Projects in Middle East\", in\n8th International Conference on Risk Analysis and Hazard Mitigation,\nBrebbia, C. (ed.), 175-187, Wessex Institute of Technology, UK 2012.", "M. E. Georgy, N. Y. Zabel, and M. E. Ibrahim, \"A balanced risk\ntreatment for construction projects.\" In 7th International Conference for\nStructural Engineering and Construction, Honolulu, USA, 2013.", "N. Y. Zabel. \"Risk Management of Pipeline Infrastructure Projects in\nEgypt \", MSc. Thesis, Faculty of Engineering, Cairo University, Giza,\nEgypt, 2007.", "L. K. Kaetzel, \"Highway Concrete (Hwycon) Expert System in the\nClassroom\" in Third Annual Undergraduate Faculty Enhancement\nSymposium on Teaching the Materials Science, Engineering, and Field\nAspects of Concrete, Cincinnati, Illinois, US, 1995.", "D. Merritt, \"Building Expert Systems in Prolog,\" Amazi.inc, 5861\nGreentree Road Lebanon, OH 45036 U.S., 2000.", "Y. F. Bazan, \"An Expert System For Material Claims Guidance\", Doctor\nof Philosophy Thesis, Structural Engineering Department, The Cairo\nUniversity In Giza, Egypt, 2001."]}

A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. Paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords

Knowledge Management, Pipeline Projects, Risk Mismanagement., Expert System

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