Backfill mining is one of the most important technical means for controlling strata movement and reducing surface subsidence and environmental damage during exploitation of underground coal resources. Ensuring the sta...Backfill mining is one of the most important technical means for controlling strata movement and reducing surface subsidence and environmental damage during exploitation of underground coal resources. Ensuring the stability of the backfill bodies is the primary prerequisite for maintaining the safety of the backfilling working face, and the loading characteristics of backfill are closely related to the deformation and subsidence of the roof. Elastic thin plate model was used to explore the non-uniform subsidence law of the roof, and then the non-uniform distribution characteristics of backfill bodies’ load were revealed. Through a self-developed non-uniform loading device combined with acoustic emission (AE) and digital image correlation (DIC) monitoring technology, the synergistic dynamic evolution law of the bearing capacity, apparent crack, and internal fracture of cemented coal gangue backfills (CCGBs) under loads with different degrees of non-uniformity was deeply explored. The results showed that: 1) The uniaxial compressive strength (UCS) of CCGB increased and then decreased with an increase in the degree of non-uniformity of load (DNL). About 40% of DNL was the inflection point of DNL-UCS curve and when DNL exceeded 40%, the strength decreased in a cliff-like manner;2) A positive correlation was observed between the AE ringing count and UCS during the loading process of the specimen, which was manifested by a higher AE ringing count of the high-strength specimen. 3) Shear cracks gradually increased and failure mode of specimens gradually changed from “X” type dominated by tension cracks to inverted “Y” type dominated by shear cracks with an increase in DNL, and the crack opening displacement at the peak stress decreased and then increased. The crack opening displacement at 40% of the DNL was the smallest. This was consistent with the judgment of crack size based on the AE b-value, i. e., it showed the typical characteristics of “small b-value-large crack and large b-value-small crack”. The research results are of significance for preventing the instability and failure of backfill.展开更多
单个较大非均匀超图聚类旨在将非均匀超图包含的节点划分为多个簇,使得同一簇内的节点更相似,而不同簇中的节点更不相似,具有广泛的应用场景。目前,最优的基于超图神经网络的非均匀超图聚类方法CIAH(co-cluster the interactions via at...单个较大非均匀超图聚类旨在将非均匀超图包含的节点划分为多个簇,使得同一簇内的节点更相似,而不同簇中的节点更不相似,具有广泛的应用场景。目前,最优的基于超图神经网络的非均匀超图聚类方法CIAH(co-cluster the interactions via attentive hypergraph neural network)虽然较好地学习了非均匀超图的关系信息,但仍存在两点不足:(1)对于局部关系信息的挖掘不足;(2)忽略了隐藏的高阶关系。因此,提出一种基于多尺度注意力和动态超图构建的非均匀超图聚类模型MADC(non-uniform hypergraph clustering combining multi-scale attention and dynamic construction)。一方面,使用多尺度注意力充分学习了超边中节点与节点之间的局部关系信息;另一方面,采用动态构建挖掘隐藏的高阶关系,进一步丰富了超图特征嵌入。真实数据集上的大量实验结果验证了MADC模型在非均匀超图聚类上的聚类准确率(accuracy,ACC)、标准互信息(normalized mutual information,NMI)和调整兰德指数(adjusted Rand index,ARI)均优于CIAH等所有Baseline方法。展开更多
精准的风电功率预测对于电力系统安全稳定运行具有十分重要的现实意义。受到尾流效应等因素影响,风电场内各风机之间存在着复杂的关联特性。现有研究忽略了时空关联特性的动态变化过程,传统图结构的二元关系表示方法也难以精确的表征风...精准的风电功率预测对于电力系统安全稳定运行具有十分重要的现实意义。受到尾流效应等因素影响,风电场内各风机之间存在着复杂的关联特性。现有研究忽略了时空关联特性的动态变化过程,传统图结构的二元关系表示方法也难以精确的表征风电机组间复杂多元的时空关系,导致风机间的时空特征难以精确捕捉。同时考虑到深度学习模型可解性差的问题与尾流效应对风电功率的影响,该文提出一种基于尾流关联的动态超图风电功率超短期预测方法。首先,将各风机视为节点,各风机历史功率作为特征输入,风电机组的空间位置和多元复杂关系作为超边,沿着时间维度构建风电机组动态超图表示结构。然后,结合每个时刻的风向数据与风机信息,根据Jensen尾流模型原理,以射线法的形式构建基于尾流关联的动态超图。在此基础上,针对动态超图的特殊数据结构,构建基于动态超图卷积的时空聚合特征提取模块与双向长短时记忆网络(bidirectional long short-term memory,BiLSTM)的时空特征拟合模块,提取动态时空特征并实现精准预测,最后,基于真实风电数据进行实验分析,从多维度验证该方法的优越性。展开更多
基金Project(51925402) supported by the National Natural Science Foundation for Distinguished Young Scholars of ChinaProject(202303021211060) supported by the Natural Science Research General Program for Shanxi Provincial Basic Research Program,China+1 种基金Project(U22A20169) supported by the Joint Fund Project of National Natural Science Foundation of ChinaProjects(2021SX-TD001, 2021SX-TD002) supported by the Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering,China。
文摘Backfill mining is one of the most important technical means for controlling strata movement and reducing surface subsidence and environmental damage during exploitation of underground coal resources. Ensuring the stability of the backfill bodies is the primary prerequisite for maintaining the safety of the backfilling working face, and the loading characteristics of backfill are closely related to the deformation and subsidence of the roof. Elastic thin plate model was used to explore the non-uniform subsidence law of the roof, and then the non-uniform distribution characteristics of backfill bodies’ load were revealed. Through a self-developed non-uniform loading device combined with acoustic emission (AE) and digital image correlation (DIC) monitoring technology, the synergistic dynamic evolution law of the bearing capacity, apparent crack, and internal fracture of cemented coal gangue backfills (CCGBs) under loads with different degrees of non-uniformity was deeply explored. The results showed that: 1) The uniaxial compressive strength (UCS) of CCGB increased and then decreased with an increase in the degree of non-uniformity of load (DNL). About 40% of DNL was the inflection point of DNL-UCS curve and when DNL exceeded 40%, the strength decreased in a cliff-like manner;2) A positive correlation was observed between the AE ringing count and UCS during the loading process of the specimen, which was manifested by a higher AE ringing count of the high-strength specimen. 3) Shear cracks gradually increased and failure mode of specimens gradually changed from “X” type dominated by tension cracks to inverted “Y” type dominated by shear cracks with an increase in DNL, and the crack opening displacement at the peak stress decreased and then increased. The crack opening displacement at 40% of the DNL was the smallest. This was consistent with the judgment of crack size based on the AE b-value, i. e., it showed the typical characteristics of “small b-value-large crack and large b-value-small crack”. The research results are of significance for preventing the instability and failure of backfill.
文摘多行为推荐(multi-behavior recommendation,MBR)在互联网平台中愈发重要,但现有方法仍面临两大挑战:a)无法刻画用户不同行为下的复杂兴趣偏好;b)难以建模不同行为间的相互关系。基于此,提出一种对比学习增强的多行为超图神经网络模型(multi-behavior hypergraph neural network model enhanced with contrastive lear-ning,MBHCL),在建模用户复杂多类型交互的同时,结合对比学习捕获行为间共性与差异,以获取更优嵌入表示,缓解冷启动与数据稀疏问题。具体地,MBHCL首先构建用户-项目多行为交互超图,以刻画用户对项目不同维度的偏好;其次设计三个对比任务整合单行为表示,通过捕捉行为间的共性与差异获取全面用户兴趣偏好。最终,MBHCL在四个真实场景数据集上进行对比实验。结果表明,在Tmall和BeiBei数据集上,HIT和NDCG指标有至少4.8%的提升,在Kuairand和Yelp数据集上,HIT和NDCG指标至少提升3.6%,并通过消融实验验证了各模块的有效性,同时显著改善了冷启动用户推荐效果。
文摘精准的风电功率预测对于电力系统安全稳定运行具有十分重要的现实意义。受到尾流效应等因素影响,风电场内各风机之间存在着复杂的关联特性。现有研究忽略了时空关联特性的动态变化过程,传统图结构的二元关系表示方法也难以精确的表征风电机组间复杂多元的时空关系,导致风机间的时空特征难以精确捕捉。同时考虑到深度学习模型可解性差的问题与尾流效应对风电功率的影响,该文提出一种基于尾流关联的动态超图风电功率超短期预测方法。首先,将各风机视为节点,各风机历史功率作为特征输入,风电机组的空间位置和多元复杂关系作为超边,沿着时间维度构建风电机组动态超图表示结构。然后,结合每个时刻的风向数据与风机信息,根据Jensen尾流模型原理,以射线法的形式构建基于尾流关联的动态超图。在此基础上,针对动态超图的特殊数据结构,构建基于动态超图卷积的时空聚合特征提取模块与双向长短时记忆网络(bidirectional long short-term memory,BiLSTM)的时空特征拟合模块,提取动态时空特征并实现精准预测,最后,基于真实风电数据进行实验分析,从多维度验证该方法的优越性。
