Titlebook: 12th World Conference “Intelligent System for Industrial Automation” (WCIS-2022); Volume 2 R. A. Aliev,Nodirbek Rustambekovich Yusupbekov,S

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https://doi.org/10.1007/978-3-663-05124-4unoff was chosen as the output variable. The Coefficient of Determination (R.) and Root Mean Square Error (RMSE) were used to test the accuracy of the models. From the results, it was found that the Cascade Feedforward Neuron Network was the most stable during the testing phase, as measured by the s

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A Bert Model with Deep Learning Approach in Natural Language Processing (NLP), Profile (MSP) approach. Our preliminary tests demonstrated the capability of this system to precisely calculate and render E-fields with a frame rate of 6 Hz (6 frames/second). Furthermore, we utilized two z-elements from the 3-axis coils to form a figure of eight coil type and utilized it for supr

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Duodenitis

Structure of a Pragmatically-Oriented Model of an Agglutinative Natural Language Exemplified with T of language. This development depends on the appropriation of functions that exist not only in genes but are rooted in the local culture. The child learns to speak in a communicative, prelinguistic context and simultaneously learns what is customary and reasonable in his particular social setting a

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