针对现有算法聚类精度不高、处理离群点能力较差以及不能实时检测数据流变化的缺陷,提出一种基于密度与近邻传播融合的数据流聚类算法.该算法采用在线/离线两阶段处理框架,通过引入微簇衰减密度来精确反映数据流的演化信息,并采用在线...针对现有算法聚类精度不高、处理离群点能力较差以及不能实时检测数据流变化的缺陷,提出一种基于密度与近邻传播融合的数据流聚类算法.该算法采用在线/离线两阶段处理框架,通过引入微簇衰减密度来精确反映数据流的演化信息,并采用在线动态维护和删减微簇机制,使算法模型更符合原始数据流的内在特性.同时,当模型中检测到新的类模式出现时,采用一种改进的加权近邻传播聚类(Weighted and hierarchical affinity propagation,WAP)算法对模型进行重建,因而能够实时检测到数据流的变化,并能给出任意时间的聚类结果.在真实数据集和人工数据集上的实验表明,该算法具有良好的适用性、有效性和可扩展性,能够取得较好的聚类效果.展开更多
Ball milling is widely used in industry to mill particulate material.The primary purpose of this process is to attain an appropriate product size with the least possible energy consumption.The process is also extensiv...Ball milling is widely used in industry to mill particulate material.The primary purpose of this process is to attain an appropriate product size with the least possible energy consumption.The process is also extensively utilised in pharmaceuticals for the comminution of the excipients or drugs.Surprisingly,for ball mill,little is known concerning the mechanism of size reduction.Traditional prediction approaches are not deemed useful to provide significant insights into the operation or facilitate radical step changes in performance.Therefore,the discrete element method(DEM)as a computational modelling approach has been used in this paper.In previous research,DEM has been applied to simulate breaking behaviour through the impact energy of all ball collisions as the driving force for fracturing.However,the nature of pharmaceutical material fragmentation during ball milling is more complex.Suitable functional equations which link broken media and applied energy do not consider the collision of particulate media of different shapes or collisions of particulate media(such as granules)with balls and rotating mill drum.This could have a significant impact on fragmentation.Therefore,this paper aimed to investigate the fragmentation of bounded particles into DEM granules of different shape/size during the ball milling process.A systematic study was undertaken to explore the effect of milling speed on breakage behaviour.Also,in this study,a combination of a density-based clustering method and discrete element method was employed to numerically investigate the number and size of the fragments generated during the ball milling process over time.It was discovered that the collisions of the ball increased proportionally with rotation speed until reaching the critical rotation speed.Consequently,results illustrate that with an increase of rotation speed,the mill power increased correspondingly.The caratacting motion of mill material together with balls was identified as the most effective regime regarding the fragmentation,and展开更多
为提高油浸式电力变压器故障状态评估的准确性,结合局部密度聚类(local density clustering,LDC)算法和三比值法提出一种变压器故障状态评估方法——以油中溶解气体为研究对象,对气体数据进行LDC处理,以最后聚类结果作为故障状态评估模...为提高油浸式电力变压器故障状态评估的准确性,结合局部密度聚类(local density clustering,LDC)算法和三比值法提出一种变压器故障状态评估方法——以油中溶解气体为研究对象,对气体数据进行LDC处理,以最后聚类结果作为故障状态评估模型及结合三比值法对新数据进行故障评估。该方法在弥补聚类方法无法准确反映故障状态和三比值法编码不全、编码太片面等不足的同时,在变压器状态发生变化时能随着新数据的输入自主修正故障状态评估模型。不同实验结果表明该方法用在变压器故障评估中,具有较高的故障评估准确率,并且当出现未知故障时能有效修正所搭建故障状态评估模型,可以在一定程度上反映变压器故障状态,保证变压器正常、安全运行。展开更多
文摘针对现有算法聚类精度不高、处理离群点能力较差以及不能实时检测数据流变化的缺陷,提出一种基于密度与近邻传播融合的数据流聚类算法.该算法采用在线/离线两阶段处理框架,通过引入微簇衰减密度来精确反映数据流的演化信息,并采用在线动态维护和删减微簇机制,使算法模型更符合原始数据流的内在特性.同时,当模型中检测到新的类模式出现时,采用一种改进的加权近邻传播聚类(Weighted and hierarchical affinity propagation,WAP)算法对模型进行重建,因而能够实时检测到数据流的变化,并能给出任意时间的聚类结果.在真实数据集和人工数据集上的实验表明,该算法具有良好的适用性、有效性和可扩展性,能够取得较好的聚类效果.
基金supported by the Career-FIT Fellowshipsfunded through European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.713654supported by ACCORD(ITMS project code:313021X329),funded through the European Regional Development Fund.
文摘Ball milling is widely used in industry to mill particulate material.The primary purpose of this process is to attain an appropriate product size with the least possible energy consumption.The process is also extensively utilised in pharmaceuticals for the comminution of the excipients or drugs.Surprisingly,for ball mill,little is known concerning the mechanism of size reduction.Traditional prediction approaches are not deemed useful to provide significant insights into the operation or facilitate radical step changes in performance.Therefore,the discrete element method(DEM)as a computational modelling approach has been used in this paper.In previous research,DEM has been applied to simulate breaking behaviour through the impact energy of all ball collisions as the driving force for fracturing.However,the nature of pharmaceutical material fragmentation during ball milling is more complex.Suitable functional equations which link broken media and applied energy do not consider the collision of particulate media of different shapes or collisions of particulate media(such as granules)with balls and rotating mill drum.This could have a significant impact on fragmentation.Therefore,this paper aimed to investigate the fragmentation of bounded particles into DEM granules of different shape/size during the ball milling process.A systematic study was undertaken to explore the effect of milling speed on breakage behaviour.Also,in this study,a combination of a density-based clustering method and discrete element method was employed to numerically investigate the number and size of the fragments generated during the ball milling process over time.It was discovered that the collisions of the ball increased proportionally with rotation speed until reaching the critical rotation speed.Consequently,results illustrate that with an increase of rotation speed,the mill power increased correspondingly.The caratacting motion of mill material together with balls was identified as the most effective regime regarding the fragmentation,and
文摘为提高油浸式电力变压器故障状态评估的准确性,结合局部密度聚类(local density clustering,LDC)算法和三比值法提出一种变压器故障状态评估方法——以油中溶解气体为研究对象,对气体数据进行LDC处理,以最后聚类结果作为故障状态评估模型及结合三比值法对新数据进行故障评估。该方法在弥补聚类方法无法准确反映故障状态和三比值法编码不全、编码太片面等不足的同时,在变压器状态发生变化时能随着新数据的输入自主修正故障状态评估模型。不同实验结果表明该方法用在变压器故障评估中,具有较高的故障评估准确率,并且当出现未知故障时能有效修正所搭建故障状态评估模型,可以在一定程度上反映变压器故障状态,保证变压器正常、安全运行。
