Results 21 to 30 of about 15,391 (164)
Kongjian kexue xuebao, 2023 对在轨卫星的运行状态进行监测、分析以及异常检测是卫星在轨运行管理的重要内容。预测卫星遥测参数序列的变化趋势，对卫星异常检测与处置、保障安全运行非常必要。针对目前对于周期性不明显且具有多种变化特征的遥测参数预测精确度不够的问题，本文引入对遥测参数的预测有辅助作用的因素作为协变量，提出了基于改进组合机器学习的预测模型。该模型使用全局模型和局部模型分别获取遥测参数序列的趋势特征和局部不规则波动特征，并采用改进的注意力机制捕获多维参数之间的关联关系，提高了预测精度。此模型可以提供点预测和区间预测的结果 ...
姜 改新, 刘 玉荣
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High Performance Catalyst Design by Artificial Intelligence for Acetylene Hydrochlorination
Rare Metals, EarlyView.ABSTRACT The rapid development of artificial intelligence (AI) has brought transformative contributions to society, revolutionizing various fields through its advanced computational capabilities and data‐driven approaches. In the field of materials science, AI has become a powerful tool that significantly accelerates the discovery of new materials by ...
Yuan Zhou +12 more
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The vibration environment prediction method based on OPAX
Xibei Gongye Daxue Xuebao, 2022 准确获得飞机结构及机载设备的振动环境至关重要, 传统的振动环境预计方法预计准确度低, 可能会导致后期振动环境试验过试验或欠试验的问题。创新性地提出了一种基于扩展工况传递路径分析(OPAX)的振动环境预计方法, 采用实测数据搭建振动环境预计模型, 再利用该模型对新工况下的振动环境进行预计。试验室环境下, 搭建了某型飞机典型设备舱振动测试系统, 基于OPAX方法搭建了机载设备的振动环境预计模型, 并对其预计准确度进行了验证。对比预计结果与试验结果, 得到: ①新工况下模型预计均方根值与试验测试均方根值相比,
LI Yixuan +3 more
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Rare Metals, EarlyView.ABSTRACT High‐entropy alloys (HEAs) have emerged as a transformative class of materials distinguished by their complex chemical compositions, unique microstructures, and remarkable mechanical and functional properties. Traditionally, the discovery and optimization of HEAs have relied on conventional methods, including trial‐and‐error experimentation ...
Chrispin Ouko Zamzu +2 more
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Wildlife Letters, EarlyView.Climate change drives shifts in suitable habitats for Eurasian lynx and its prey (hare, roe deer) in Mohe, Daxing'anling Mountains. Under RCP scenarios, moderate warming (RCP4.5) promotes substantial habitat expansion, while high‐emission conditions (RCP8.5) lead to strong expansion in the 2050s but slower gains and partial contraction by the 2070s ...
Binglian Liu +5 more
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Functional Ecology, EarlyView.Read the free Plain Language Summary for this article on the Journal blog. Abstract Decomposition is the transformation of dead organic matter into its inorganic constituents. In most biomes, decomposition rates can be accurately predicted with simple mathematical models, but these models have long under‐predicted decomposition in globally extensive ...
Heather L. Throop +8 more
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Zhongguo cuzhong zazhi摘要： 预测模型是用来预测个体发生目标事件概率或预测结局值的统计模型。预测模型结果可视化展现是开发预测模型全流程中必不可少的一部分。良好的预测模型展现形式不仅可以使预测结果具有更好的可读性、可解释性，也在很大程度上决定了其使用方式和便利性。本文将详细介绍各种预测模型的展现形式，并阐述各自的优缺点。随后结合脑血管病临床预测模型研究，通过研究示例逐一介绍不同展现形式在脑血管病研究中的应用。 Abstract: A prediction model is a statistical model ...
金奥铭，谷鸿秋
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Functional Ecology, EarlyView.Read the free Plain Language Summary for this article on the Journal blog. Abstract Forests worldwide are increasingly impacted by drought due to climate change, prompting plants to adapt through dehydration tolerance (DT) and avoidance (DA), two distinct physiological strategies.
Xingyun Liang +11 more
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Zhongguo shiyan zhenduanxue, 2018 目的构建2型糖尿病发病风险预测模型。方法在体检人群中招募糖尿病患者53人,非糖尿病患者93人,体检的同时进行相应的基因检测,并填写健康体检自测问卷,收集全部数据采用XGBoost构建2型糖尿病预测模型。结果模型预测的准确率是86.6%,特征重要性评估结果显示,对模型贡献前三名的变量依次是血糖、甘油三酯和SLC30A8基因rs13266634-C位点的等位基因。结论 XGBoost糖尿病发病风险预测模型具有很强的预测能力。
张洪侠 +13 more
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A link between increased temperature and avian body condition in a logged tropical forest
Conservation Biology, EarlyView.Abstract The combined effects of anthropogenic disturbances, such as logging and climate change, remain poorly understood; yet, they are the main threats to tropical biodiversity. Most tropical African countries lack long‐term climate data, so climate impacts on biodiversity cannot be assessed.
Moreen Uwimbabazi +7 more
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