Peculiarities of the Hybrid Model Built Using Parallel Data

A hybrid model built using parallel data combines the prerequisites of two or more models in its predecessors, it becomes necessary to reduce the number of these predecessors. For this, we consider it necessary to investigate the cause-and-effect relationships between the preconditions, which are th...

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Bibliographic Details
Published in2022 7th International Conference on Mathematics and Computers in Sciences and Industry (MCSI) pp. 66 - 70
Main Authors Phkhovelishvili, Merab, Archvadze, Natela, Gasitashvili, Zurab
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2022
Subjects
approximate accuracy
Computational modeling
Computers
Data models
Industries
Mathematical models
Parallel data
prediction models
Predictive models
probability of prediction success component
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DOI10.1109/MCSI55933.2022.00018

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Summary:A hybrid model built using parallel data combines the prerequisites of two or more models in its predecessors, it becomes necessary to reduce the number of these predecessors. For this, we consider it necessary to investigate the cause-and-effect relationships between the preconditions, which are the "main" and cause other precursors, which should become the subject of research and the main decisive factor in the process of making predictions. A hybrid model can only be learned from "necessary" models, that is why it is important to study the predecessor, to identify the "necessary" and "sufficient" predecessor.
DOI:10.1109/MCSI55933.2022.00018