IEEE

Comparison of Random Forest and SARIMA Methods Optimized with Genetic Algorithm for Wind Forecasting

Abstract: In this work, the Random Forest and SARIMA methods were used, both optimized through genetic algorithms, with the purpose of forecasting wind speed and, consequently, energy production. The ...
InfoQ

Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to ...
IEEE

Optimized PI/PD/PID Controller Design for DC Motor Speed Control: A Comparative Study of Random Forest-Based Tuning & Classical Methods

Abstract: This Study explores ways to improve the speed of DC motors through comparison of traditional tuning methods, viz. Ziegler-Nichols and Cohen-Coon with a machine learning approach using Random ...