| Issue |
E3S Web of Conf.
Volume 402, 2023
International Scientific Siberian Transport Forum - TransSiberia 2023
|
|
|---|---|---|
| Article Number | 03034 | |
| Number of page(s) | 5 | |
| Section | Mathematical Modeling, IT, Industrial IoT, AI, and ML | |
| DOI | https://doi.org/10.1051/e3sconf/202340203034 | |
| Published online | 19 July 2023 | |
Development of the architecture of a transformer-based neural network model to automate delivering judgments in bankruptcy cases
T.F. Gorbachev Kuzbass State Technical University, 650000 Kemerovo, Russia
* Corresponding author: pylovpa@kuzstu.ru
Delivering judgments is one of the brightest examples of solving a creative problem, which implies not only the analysis of data presented in natural language, but also the verification of the compliance of the input information with legal norms and rules. Automation of this process requires the creation of such a language model of machine learning that would allow processing natural language and delivering judgments based on the legal framework, thereby completely replacing the position of a judge. Serious functional requirements are imposed on such an intelligent system, which describe the system of constraints for the architecture of a machine learning model in a formalized mathematical language. This article is devoted to defining the rules for building an applied artificial intelligence model that would automate the process of delivering judgments in bankruptcy cases.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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