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利用机器学习和 SHapley 加法计划，以不同的时间分辨率评估真实现场天气条件下矿车的生产率

IF 2.7 3区 工程技术 Q3 ENVIRONMENTAL SCIENCES
International Journal of Mining Reclamation and Environment Pub Date : 2024-05-06 DOI:10.1080/17480930.2024.2348877
Chengkai Fan, Chathuranga Balasooriya Arachchilage, Na Zhang, Bei Jiang, Wei Victor Liu
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引用次数: 0

摘要

更新后的摘要缩短至约 100 字，如下所示：这项研究建立了卡车生产率预测模型，其中纳入了不同时间分辨率的真实现场天气条件....。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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Machine learning with SHapley additive exPlanations for evaluating mine truck productivity under real-site weather conditions at varying temporal resolutions
The updated abstract, shortened to about 100 words, is shown below: This study built truck productivity prediction models incorporating real-site weather conditions at varying temporal resolutions....
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来源期刊
International Journal of Mining Reclamation and Environment
International Journal of Mining Reclamation and Environment ENVIRONMENTAL SCIENCES-MINING & MINERAL PROCESSING
CiteScore
5.70
自引率
8.30%
发文量
30
审稿时长
>12 weeks
期刊介绍： The International Journal of Mining, Reclamation and Environment published research on mining and environmental technology engineering relating to metalliferous deposits, coal, oil sands, and industrial minerals. We welcome environmental mining research papers that explore: -Mining environmental impact assessment and permitting- Mining and processing technologies- Mining waste management and waste minimization practices in mining- Mine site closure- Mining decommissioning and reclamation- Acid mine drainage. The International Journal of Mining, Reclamation and Environment welcomes mining research papers that explore: -Design of surface and underground mines (economics, geotechnical, production scheduling, ventilation)- Mine planning and optimization- Mining geostatics- Mine drilling and blasting technologies- Mining material handling systems- Mine equipment
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