When one diagnostic expert system fails in solving problems alone, how can it get information available to improve itself from another similar diagnostic expert system ? This paper presents the interoperation environment to support the process. First, inference primitive structure templates have been presented to share inference structures between two diagnostic expert systems. Next, the cooper...

Diabetes is a chronic disease. The World Health Organization predicts that Indonesia's number of diabetic patients will continue to increase significantly 16.7 million in 2045. As early prevention, diagnosis needed anticipate more severe diabetes. This study aims build an expert system for detecting diabetes using web-based forward chaining method. built by collecting indications from experts f...

Expert systems are used for evaluating the actual state and future behavior of insulating systems of high voltage electrical machines and equipment. Several rule-based expert systems have been developed in cooperation with top diagnostic workplaces in the Czech Republic for this purpose. The IZOLEX expert system evaluates diagnostic measurement data from commonly used off-line diagnostic method...

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to n...

This paper discusses an application of failure-driven learning to the construction of the knowledge base of a diagnostic expert system. Diagnosis heuristics (i.e., efficient rules which encode empirical associations between atypical device behavior and device failures) are learned from information implicit in device models. This approach is desireable since less effort is required to obtain inf...