Journal Article10.1016/j.ins.2023.03.004
Shield attitude prediction based on Bayesian-LGBM machine learning
Hong Chen,Xinyi Li,Zongbao Feng,Lei Wang,Yawei Qin,Miroslaw J. Skibniewski,Zhenhua Chen,Yang Liu +7 more
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TL;DR: Wang et al. as mentioned in this paper proposed an intelligent method to predict the shield attitude based on a Bayesian-light gradient boosting machine (LGBM) model, which includes 29 parameters that impact the attitude and 6 parameters that represent the attitude.
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About: This article is published in Information Sciences. The article was published on 01 Mar 2023. The article focuses on the topics: Computer science & Bayesian probability.
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Citations
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A comprehensive machine learning-coupled response surface methodology approach for predictive modeling and optimization of biogas potential in anaerobic Co-digestion of organic waste
Aqueel Ahmad,Ashok Yadav,Achhaibar Singh,Dinesh Kumar Singh +3 more
TL;DR: This study develops a machine learning-coupled response surface methodology approach to predict and optimize biogas production in anaerobic co-digestion of organic waste, achieving high accuracy with XGB model and identifying optimal parameters for maximum biogas yield.
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Optimization of high-performance concrete mix ratio design using machine learning
TL;DR: In this article , a hybrid intelligent framework for multi-objective optimization based on random forest (RF) and the non-dominated sorting genetic algorithm version II (NSGA-II) is developed to efficiently predict concrete durability and optimize the concrete mix ratio.
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Building information modelling-enabled multi-objective optimization for energy consumption parametric analysis in green buildings design using hybrid machine learning algorithms
Yang Liu,Tiejun Li,Wensheng Xu,Qiang Wang,Hao Huang,Baojie He +5 more
TL;DR: This study develops a hybrid machine learning algorithm using BIM-DesignBuilder, Grey wolf optimization, random forest, and NSGA-II to optimize green building design parameters, achieving 16.6% reduction in life cycle carbon emission and 2.0% reduction in economic cost.
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Safety evaluation of buildings adjacent to shield construction in karst areas: An improved extension cloud approach
TL;DR: Wang et al. as discussed by the authors proposed a safety evaluation standard for buildings adjacent to shield construction in karst areas, and a safety risk assessment method based on optimal cloud entropy are proposed.
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References
A novel stacked generalization ensemble-based hybrid LGBM-XGB-MLP model for Short-Term Load Forecasting
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TL;DR: A novel stacking ensemble-based algorithm is proposed that copes with the stochastic variations of the load demand using a stacked generalization approach and is validated using two datasets from different locations: Malaysia and New England.
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Support vector machine applied to settlement of shallow foundations on cohesionless soils
TL;DR: In this article, a support vector machine (SVM) was used to predict the settlement of shallow foundations on cohesionless soil, and a thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement.
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Energy consumption prediction and diagnosis of public buildings based on support vector machine learning: A case study in China
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Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete
TL;DR: Wang et al. as mentioned in this paper used three ensemble machine learning (EML) models: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient boosting machine (LGBM) to predict concrete creep behavior.