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Abstract

Business intelligence (BI) has been successful in eliminating the traditional decision support systems at Gulf Shores Company (GSC) to improve efficiency and effectiveness in service delivery and eliminate human errors. Such improved organizations are better prepared to respond quickly to threats and opportunities. Artificial intelligence (AI) supports an organization’s BI process by simplifying them and making them more cost-effective so that, under certain conditions, automated decisions and alerts can be used. Introducing AI into GSC processes would also give them the capability of making decisions in real time. GSC could implement the BI/AI combination in complex settings to address a wide range of risks specific to their industry. The case study describes the logic for implementing AI in petroleum industries, based on an intelligent system that helps offshore platforms start up, and explains how it can be applied in other industries such as medical billing.

Keywords

Business intelligence artificial intelligence robotics intelligent system neural networks fuzzy logic

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References

Advanced Industrial Science and Technology (2009). Successful development of a robot with appearance and performance similar to human—For the entertainment industry. National Institute of Advanced Industrial Science and Technology. Retrieved 8 March 2013, from http://www.aist.go.jp/aist_e/latest_research/2009/20090513/20090513.html

Domaine

(2006). Robotics. Minneapolis, MN: Lerner.

Gallant

S.I.

(1993). Neural network learning and expert systems. Cambridge, MA: MIT Press.

Kosko

(1992). Neural networks and fuzzy systems: A dynamical systems approach to machine intelligence. Englewood Cliffs, NJ: Prentice Hall.

Liebowitz

(2006). Strategic intelligence: Business intelligence, competitive intelligence, and knowledge management. Boca Raton, FL: Auerbach.

Mohaghegh

(n.d.). Recent development in application of artificial intelligence in petroleum engineering. Retrieved 15 September 2012, from http://www.pe.wvu.edu/Publications/Pdfs/89033.pdf

Partridge

(2010). Robotics. New York, NY: Wilson.

Simpson

P. K.

(1990). Artificial neural systems: Foundations, paradigms, applications, and implementations. New York, NY: Pergamon Press.

Turban

Sharda

(2011). Decision support and business intelligence systems (9th ed.). Boston, MA: Prentice Hall.

10.

Zurada

J.M.

(1992). Introduction to artificial neural systems. St. Paul, MN: West.