Abstract
An important measure of the success of the expert system’s implementation is its users’ acceptance. An expert system doesn’t have to provide very good conclusions when its use is very complex and time-consuming both in learning and in use. From the user’s point of view, it is important that working with the system is easy and easy to understand. It is appropriate for the system to be able to correct the most common user errors. It is necessary to note that expert systems can also be used for training new experts when workers are familiarized with evaluating input data and the possible conclusions that may result from them with the help of the explanatory mechanism of the system. We cannot get complete information to solve most problems. It remains only to fill in the information data gaps while considering the possibility of error. During processing, the effects of stored knowledge and probabilities are combined. In the post, the main problem was the determined amount of tyres provided to each driver for the race. The work deals with t collecting and processing data on the climate, the type of circuit and the subsequent use of this data in motorsport to reduce the number of tyres provided for the benefit of expert systems.
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This work was supported by the projects VEGA 1/0268/22, KEGA 038TUKE-4/2022 granted by the Ministry of Education, Science, Research and Sport of the Slovak Republic.
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Knapčíková, L., Behúnová, A., Husár, J., Tauberová, R., Martiček, M. (2024). Enhancing Circular Economy Using Expert Systems. In: Perakovic, D., Knapcikova, L. (eds) Future Access Enablers for Ubiquitous and Intelligent Infrastructures. FABULOUS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-031-50051-0_6
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