INTELLIGENT INTERFACE AGENT FOR AGRICULTURAL EXPERT SYSTEMS

The acceptance of an expert system by the end user has been regarded as one of the major criteria of expert systems success. Expert systems are characterized by its requirement for heavy and complex interaction with the end user. This paper introduces an approach for interacting with multiple expert system applications through a unified domain-specific intelligent interface agent. The proposed intelligent interface agent communicates with different expert system applications transparently from the end user, and makes the necessary actions when needed. This approach increases the usability of expert system applications and introduces a new methodology for expert systems development using multi-agent systems (MAS). The proposed approach has been applied by the Central Laboratory for Agricultural Expert Systems (CLAES) where two expert system applications – diagnosis and irrigation – have been interfaced by an intelligent interface agent. According to our proposed approach a number of advantages have been accomplished at both practical and theoretical levels

A Comparative Analysis of Design Techniques for the Construction of an Expert System for Aircraft Engine Diagnostics

The lack of knowledge and understanding of diagnostic aircraft propulsion systems causes inappropriate problem diagnosis. Because of increasing complexity, technicians are incapable of performing the necessary tasks in accordance with standard regulations. More sophisticated systems are needed today to assist the user technician in decision-making. This work provided a study of rule-based and frame-based expert system techniques to determine the most appropriate solution in the domain of complex diagnosis using large amounts of deterministic data. The study produced a framework that facilitates the diagnosing of faults on aircraft engines, thus reducing the burden on the aircraft mechanic regardless of experience level. An intelligent system, the Virtually Automated Maintenance Analysis System (V AMAS), was created as a test model. It was used to compare the relative efficiency of the different expert systems techniques and the effectiveness of expert systems. One aviation malfunction problem was identified. Information collected for the Main Ignition Malfunction was developed into question sets and coded. Six specific subsets of problems were addressed. This research compared the rule-based and frame-based knowledge representation techniques using a set of evaluation factors: computational efficiency, correctness, expressiveness, and consistency. From the analysis it was concluded that the frame based knowledge representation technique ranked higher than the rule-based representation, and is suitable for use with an expert system to represent an aircraft propulsion system \u27s deterministic data

A developed model of expert system interface (DMESI)

[[abstract]]Cognitive compatibility plays an important role in the development of the human–computer interface. A good user interface will lead to better user/expert system interaction and task performance. In this study, we examined what and how cognitive types affect problem-solving and analyzed the theoretical development of the relationship between human cognition and the use of intelligent machines in the domain of maintenance. The implementation of the knowledge acquisition (KA) presented the development process of the maintenance protocol which derived from using ICAM DEFinition0 (IDEF0) and Data Flow Diagram (DFD). From the maintenance process modeling, the formal representation of what the user does with the resulting interface can be defined. The knowledge base of the system is represented by a fault decision tree diagram, and is incorporated to communicate between the maintainers and the computer. Furthermore, we also evaluated and compared the effectiveness of expert system interface with the traditional maintenance handbook. As a case study, a fault recovery expert system for the Maintenance Department of the diesel engine bus system of Taipei City has been developed. Findings of the study have important implications in expert system interface design, including the specific features of changeability, traceability, plenitude, and qualitative description in this maintenance area