A Comprehensive Review of the Tunicate Swarm Algorithm: Variations, Applications, and Results

Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Язык: Английский

Compressive strength prediction of fiber-reinforced recycled aggregate concrete based on optimization algorithms

Frontiers in Built Environment, Год журнала: 2024, Номер 10

Опубликована: Дек. 11, 2024

With the growing emphasis on sustainable development in construction industry, fiber-reinforced recycled aggregate concrete (BFRC) has attracted considerable attention due to its superior mechanical properties and environmental benefits. However, accurately predicting compressive strength of BFRC remains a challenge because complex interaction between aggregates fiber reinforcement. This study introduces an innovative predictive framework that combines XGBoost machine learning algorithm with advanced optimization algorithms, including Seagull Optimization Algorithm (SOA), Tunicate Swarm (TSA), Mayfly (MA). The unique integration these algorithms not only improves accuracy but also optimizes model performance by enhancing parameter tuning capabilities. Experimental results demonstrated TSA-XGBoost achieved exceptional R 2 0.9847 minimum mean square error (MSE) 0.255958, outperforming other models BFRC’s strength. novel approach offers efficient accurate tool for assessing practical applications, thus supporting broader adoption construction.

Язык: Английский

Optimal sizing of hybrid energy system using an improved gazelle optimization algorithm

Electrical Engineering, Год журнала: 2024, Номер unknown

Опубликована: Дек. 28, 2024

Язык: Английский