Adaptive Processing of Technological Time Series for Forecasting Based on Neuro-Fuzzy Networks

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dc.creatorIbragimovich, Jumanov Isroil
dc.creatorBaxromovna, Melieva Mokhinur
dc.date2022-02-16
dc.date.accessioned2023-08-21T08:00:21Z
dc.date.available2023-08-21T08:00:21Z
dc.descriptionMethodological bases for identification, data processing for forecasting technological time series based on the synthesis of soft computing apparatus (dynamic models, neural networks, neuro-fuzzy networks, genetic algorithms) in various combinations have been developed. A generalized prediction optimization algorithm based on a hybrid model with mechanisms for determining and adjusting the weights of neurons, coefficients of synaptic connections, activation functions, determining the number of layers and neurons in the layers of neural networks with a rational architecture is proposed.en-US
dc.formatapplication/pdf
dc.identifierhttps://journals.researchparks.org/index.php/IJHCS/article/view/2721
dc.identifier.urihttp://dspace.umsida.ac.id/handle/123456789/16075
dc.languageeng
dc.publisherResearch Parks Publishing LLCen-US
dc.relationhttps://journals.researchparks.org/index.php/IJHCS/article/view/2721/2598
dc.sourceInternational Journal of Human Computing Studies; Vol. 4 No. 2 (2022): IJHCS; 30-35en-US
dc.source2615-8159
dc.source2615-1898
dc.source10.31149/ijhcs.v4i2
dc.subjecttechnological time seriesen-US
dc.subjectneural networken-US
dc.subjectneuro-fuzzy networken-US
dc.subjectgenetic algorithmsen-US
dc.subjecthybrid modelen-US
dc.titleAdaptive Processing of Technological Time Series for Forecasting Based on Neuro-Fuzzy Networksen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Articleen-US
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