ENERGY TRADING PLATFORM WITH A MICROSERVICES ARCHITECTURE AND AI MARKET ANALYSIS
DOI:
https://doi.org/10.24867/33BE19PopovKeywords:
Microservice, AI model, Docker, energy tradingAbstract
The paper presents the implementation of an application for automated electricity trading, which uses a trained AI model for price prediction. The solution is implemented using a microservices architecture, and the entire application is based on Docker containers.
References
[1] Sam Newma – Building Microservices: Designing Fine-Grained Systems
[2] Docker -https://www.techtarget.com/searchitoperations/definition/Docker
[3] Flask - https://flask.palletsprojects.com/en/stable/
[4] JWT Token - https://www.geeksforgeeks.org/web-tech/json-web-token-jwt/
[5] DaaS - https://www.mongodb.com/solutions/use-cases/data-as-a-service
[6] Pattern: Shared database - https://microservices.io/patterns/data/shared-database.html
[7] Linear Regression - https://www.geeksforgeeks.org/machine-learning/ml-linear-regression/
[8] reCAPTCHA - https://developers.google.com/recaptcha/docs/v3
