Abstract
An algorithmic approach based on the methods of adaptive intelligent technology for monitoring the state of objects of computer systems is considered. The approach is focused on detecting changes in the state of controlled resources of autonomous information and measurement systems: communication channel, processor, memory, and battery. An adaptive model is presented using a Bayesian classifier for estimating changes in the state of resources of autonomous information and measurement systems. The model is based on a probabilistic automaton with adaptive self-tuning. The paper describes an approach that allows increasing the duration of continuous operation of the system for monitoring environmental parameters. This approach is based on adaptive correction of primary meter readings in the event of a decrease in their accuracy due to degradation failures.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
