Abstract
With the rapid growth of data traffic from various information sources and the complexity of services increasing there is a current new trend in the ICT field that has been called the Big Data processing trend. There are a lot of up-to-day intelligent technics and systems used for overcoming this trend but the computational and data processing complexity under real-time requirements continues to be one of the important disadvantages for many engineering fields. The paper deals with an approach of Big Data stream structuring into fuzzy logic rules for fuzzy knowledge base development that has no large data processing complexity. To guarantee the correctness of the fuzzy knowledge base the metagraph theory apparatus is used based on control conflicting and duplicate rules under consideration of their logical inter-connections. Usage of the fuzzy knowledge base during Big Data stream processing helps to decrease data processing time for decision-making systems in real engineering fields.
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Globa, L., Savchuk, Z., Vasylenko, O., Siemens, E. (2021). QOS of Data Networks Analyzing Based on the Fuzzy Knowledge Base. In: Vorobiyenko, P., Ilchenko, M., Strelkovska, I. (eds) Current Trends in Communication and Information Technologies. IPF 2020. Lecture Notes in Networks and Systems, vol 212. Springer, Cham. https://doi.org/10.1007/978-3-030-76343-5_8
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