College of Computing, Engineering & Construction
Master of Science in Computer and Information Sciences (MS)
Dr. Behrooz K. Seyed-Abbassi
Dr. Roger E. Eggen
Dr. Robert Roggio
Dr. Asai Asaithambi
Dr. Mark A. Tumeo
Knowledge-based expert systems are used to enhance and automate manual processes through the use of a knowledge base and modern computing power. The traditional methodology for creating knowledge-based expert systems has many commonly encountered issues that can prevent successful implementations. Complications during the knowledge acquisition phase can prevent a knowledge-based expert system from functioning properly. Furthermore, the time and resources required to maintain a knowledge-based expert system once implemented can become problematic. There are several concepts that can be integrated into a proposed methodology to improve the knowledge-based expert system lifecycle to create a more efficient process. These methods are commonly used in other disciplines but have not traditionally been incorporated into the knowledge-based expert system lifecycle. A container-loading knowledge-based expert system was created to test the concepts in the proposed methodology. The results from the container-loading knowledge-based expert system test were compared against the historical records of thirteen container ships loaded between 2008 and 2011.
Millette, Lucien, "Improving the Knowledge-Based Expert System Lifecycle" (2012). UNF Graduate Theses and Dissertations. 407.