Danial Jahed Armaghani^1,*, Zida Liu², Hadi Khabbaz¹, Hadi Fattahi³, Diyuan Li², Mohammad Afrazi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2421-2451, 2024, DOI:10.32604/cmes.2024.052210 - 31 October 2024

Abstract Tunnel Boring Machines (TBMs) are vital for tunnel and underground construction due to their high safety and efficiency. Accurately predicting TBM operational parameters based on the surrounding environment is crucial for planning schedules and managing costs. This study investigates the effectiveness of tree-based machine learning models, including Random Forest, Extremely Randomized Trees, Adaptive Boosting Machine, Gradient Boosting Machine, Extreme Gradient Boosting Machine (XGBoost), Light Gradient Boosting Machine, and CatBoost, in predicting the Penetration Rate (PR) of TBMs by considering rock mass and material characteristics. These techniques are able to provide a good relationship between input(s)… More >

Zhihao Zheng¹, Yanbo Che^1,*, Hailian Bi¹, Dan Wu¹, Wei He²

Energy Engineering, Vol.119, No.2, pp. 637-651, 2022, DOI:10.32604/ee.2022.016661 - 24 January 2022

Abstract With the implementation of electric energy alternatives, the large-scale application of electric energy substitution represented by air-source heat pumps has replaced traditional coal-fired heating, which is beneficial for the environment and alleviates air pollution. However, the large-scale application of air-source heat pumps has brought power quality problems such as voltage sags, harmonic pollution, and three-phase imbalance to the distribution network. This paper studies the fixed-frequency and variable-frequency air-source heat pump, introduces its working principle, analyzes the mechanism of its power quality problem. Moreover, the paper establishes a simulation model for the fixed-frequency heat pump and… More >