Identifying user electric events is of significant importance for uncovering patterns in user electric consumption behavior and enhancing the level of energy efficiency management on the user side. To promptly and effectively detect electric events embedded in the electric data of the user, this paper introduces a cluster-based electric event identification model designed based on the electric current state sequence dataset. Based on extracting features from the electric current state sequence, this model treats the identification of electric events in the current sequence as a clustering partition problem utilizing the feature set derived from the electric current state sequence. To assess the model’s efficacy, two metrics were utilized: the silhouette coefficient and precision, to evaluate its performance. The experiments demonstrate that compared to the identification model for the electric event of the user based on k-means clustering, SOM clustering, and FCM clustering, the identification model for the electric event of the user based on hierarchical clustering is more effective in identifying electric events.
文章将其他收缩集族代替经典的欧几里得球族,验证其对应的Lebesgue稠密定理.利用系统的可扩张性和有界性变形等动力系统工具,研究离散动力系统生成的动力系统球族的几何及测度性质,结果表明:其他收缩集族所对应的Lebesgue稠密定理仍然成立.
为提高白光照明的显色性,利用稀土离子Ce3+、Tb3+和Eu3+设计KY(CO3)2基的白光照明材料.实验中,利用X射线衍射仪分析Ce3+、Tb3+和Eu3+掺杂KY(CO3)2后的物相结构;利用荧光光谱仪分析发光材料的光谱特性,计算相应光谱的色度坐标.实验结果表明:制备的KY(CO3)2:Ce3+、KY(CO3)2:Tb3+和KY(CO3)2:Eu3+3种发光材料均为单斜结构的纯相样品;在275 nm紫外光的激发下,3种样品分别发射出蓝紫色、绿色和红色3种不同颜色的光线.通过优化三基色的成分比例,得到色度坐标为(0.37,0.34)的高质量白光,实现光色可调的白光荧光粉的设计.
为配合国家及省的中长期发展战略,努力服务地方经济,在应用型本科院校的新工科发展战略背景下,以实际工程问题为载体,优化教学理念,深化教学内容,通过"新工科视角"对高分子物理课程的教学内容、教学模式以及教学实践进行改革与探索.本课程教学改革有效激发学生从事研究高分子材料领域的兴趣,提高学生理论联系实际,分析解决实际工程问题综合能力,有利于培养具备创新意识和创业精神的高素质应用型专门人才,对于应用型本科院校中材料工程人才教育改进发展,优化专业结构具有一定借鉴和探索意义.
针对随机系数自回归(Random Coefficient Auto-regression,RCA)时间序列模型的均值变点监测问题,引入一个窗宽参数.通过调整监测起始时刻,并插入参数的一致估计量对估计参数进行替换,给出监测统计量在原假设和备择假设下的极限分布,也提供其后验检验.最后,给出极限理论以及后验检验的模拟计算,计算结果验证该方法的有效性.
