Titlebook: Cyber-Physical Systems; Digital Technologies Alla G. Kravets,Alexander A. Bolshakov,Maxim V. Sh Book 2021 The Editor(s) (if applicable) and

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Development of a Module for Predictive Modeling of Technological Development Trendsnalyzed for more accurate and faster forecasting. A module for predictive modeling of trends in technological development is developed, algorithms for the module for predictive modeling of trends in technological development are described.

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Miscellaneous Abnormalities of the Esophagus retrieved by querying the ontology. The paper also describes the grammar for extracting technical functions in the form of a “solution-problem”. The structure and components of the subsystem for allocating the functions of technical objects are described.

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https://doi.org/10.1007/978-3-662-39704-6 with respect to its coefficients (weights). Then it is shown that the proposed approach can be simply extended on arbitrary differentiable combination models, for example, on neural networks that are differentiable and can implement arbitrary functions of gradient boosting models. Various numerical examples illustrate the proposed approach.

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https://doi.org/10.1007/978-3-319-13692-9s words sequences. The proposed method has been tested on its private data set. The proposed method has demonstrated high quality and reliability of searching for differences in two copies of the same Agreement document.

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