«Automation and Informatization of the fuel and energy complex»

Automation of intersystem integration using artificial intelligence in the tasks of data analysis, code generation and dynamic adaptation to changes

UDC: 004.048
DOI: -

Authors:

¹ National University of Oil and Gas "Gubkin University", Moscow, Russia

Keywords: generative networks, machine learning, artificial intelligence, integration, automation

Annotation:

The article presents an approach to automation of intersystem integration based on semantic data analysis and automatic code generation using artificial intelligence. Special attention is paid to dynamic adaptation mechanisms that allow the system to automatically adjust to changes in data structures and APIs without manual intervention. Thus, the threshold of technical expertise for the implementation of complex integration scenarios is significantly reduced. The developed algorithms use modern natural language processing models for semantic field matching and generative neural networks to create software code for integration. The experimental results demonstrate high accuracy of data comparison, rapid code generation based on a technical description of the interaction, and the ability to adapt to changes without the need for manual modification. The proposed solution significantly reduces the cost of maintaining and developing integration circuits in corporate environments. This opens up new opportunities for creating flexible and scalable ecosystems capable of autonomous evolution.

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