Search
Search Results
-
A novel stacking-based ensemble learning model for drilling efficiency prediction in earth-rock excavation
目的对钻进效率进行精确预测是制定土方开挖进度计划的关键。但现有预测方法多采用单个机器学**模型, 存在参数敏感性和过拟合等问题, 且往往忽略了环境因素和人员操作因素的影响。针对这些问题, 本文提出一种同时考虑多种因素综合影响的新的集成学**预测方法。
创新点1....
-
A novel stacking-based ensemble learning model for drilling efficiency prediction in earth-rock excavation
目的对钻进效率进行精确预测是制定土方开挖进度计划的关键。但现有预测方法多采用单个机器学**模型，存在参数敏感性和过拟合等问题，且往往忽略了环境因素和人员操作因素的影响。针对这些问题，本文提出一种同时考虑多种因素综合影响的新的集成学**预测方法。
创新点1....
-
A Sarsa reinforcement learning hybrid ensemble method for robotic battery power forecasting
Building a rail transit workshop with efficient data interconnection has become an inevitable trend in the transformation and development of the...
-
Ensemble machine learning for predicting the homogenized elastic properties of unidirectional composites: A SHAP-based interpretability analysis
This study aims to develop an interpretable ensemble machine learning (EML) method for predicting the homogenized elastic properties of...
-
Efficient multi-material topology optimization design with minimum compliance based on ResUNet involved generative adversarial network
Topology optimization is a common approach for material distribution in continuous structure due to its rigorous mathematical theory. However, with...
-
Intelligent diagnosis for hot-rolled strip crown with unbalanced data using a hybrid multi-stage ensemble model
To improve the smart manufacturing capabilities of strip hot rolling, based on digital twin (DT) and cyber-physical system (CPS), this paper proposes...
-
Machine learning strategies for lithostratigraphic classification based on geochemical sampling data: A case study in area of Chahanwusu River, Qinghai Province, China
Based on the complex correlation between the geochemical element distribution patterns at the surface and the types of bedrock and the powerful...