以Web of Science数据库为数据源,通过限定作者单位为中国政法大学的检索条件,检索出中国政法大学在2008—2018年发表的法学领域内的相关论文,并从总发文量、年度发文量、期刊载文量以及论文引用频次统计、作者情况等方面进行统计分析,...以Web of Science数据库为数据源,通过限定作者单位为中国政法大学的检索条件,检索出中国政法大学在2008—2018年发表的法学领域内的相关论文,并从总发文量、年度发文量、期刊载文量以及论文引用频次统计、作者情况等方面进行统计分析,揭示了中国政法大学法学领域的研究现状和发展趋势,文末结合统计分析的结果针对如何提升该校的科研水平提出了一些建议。展开更多
The transient behaviors of traditional adaptive control may be very poor in general. A practically feasible approach to improve the transient performances is the adoption of adaptive switc- hing control. For a typical...The transient behaviors of traditional adaptive control may be very poor in general. A practically feasible approach to improve the transient performances is the adoption of adaptive switc- hing control. For a typical class of nonlinear systems disturbed by random noises, mixed multiple models consisting of adaptive model and fixed models were considered to design the switching con- trol law. Under certain assumptions, the nonlinear system with the switching control law was proved rigorously to be stable and optimal A simulation example was provided to compare the performance of the switching control and the traditional adaptive control.展开更多
K-means algorithm is one of the most widely used algorithms in the clustering analysis. To deal with the problem caused by the random selection of initial center points in the traditional al- gorithm, this paper propo...K-means algorithm is one of the most widely used algorithms in the clustering analysis. To deal with the problem caused by the random selection of initial center points in the traditional al- gorithm, this paper proposes an improved K-means algorithm based on the similarity matrix. The im- proved algorithm can effectively avoid the random selection of initial center points, therefore it can provide effective initial points for clustering process, and reduce the fluctuation of clustering results which are resulted from initial points selections, thus a better clustering quality can be obtained. The experimental results also show that the F-measure of the improved K-means algorithm has been greatly improved and the clustering results are more stable.展开更多
文摘以Web of Science数据库为数据源,通过限定作者单位为中国政法大学的检索条件,检索出中国政法大学在2008—2018年发表的法学领域内的相关论文,并从总发文量、年度发文量、期刊载文量以及论文引用频次统计、作者情况等方面进行统计分析,揭示了中国政法大学法学领域的研究现状和发展趋势,文末结合统计分析的结果针对如何提升该校的科研水平提出了一些建议。
基金Supported by the National Natural Science Foundation of China (60704002)
文摘The transient behaviors of traditional adaptive control may be very poor in general. A practically feasible approach to improve the transient performances is the adoption of adaptive switc- hing control. For a typical class of nonlinear systems disturbed by random noises, mixed multiple models consisting of adaptive model and fixed models were considered to design the switching con- trol law. Under certain assumptions, the nonlinear system with the switching control law was proved rigorously to be stable and optimal A simulation example was provided to compare the performance of the switching control and the traditional adaptive control.
文摘K-means algorithm is one of the most widely used algorithms in the clustering analysis. To deal with the problem caused by the random selection of initial center points in the traditional al- gorithm, this paper proposes an improved K-means algorithm based on the similarity matrix. The im- proved algorithm can effectively avoid the random selection of initial center points, therefore it can provide effective initial points for clustering process, and reduce the fluctuation of clustering results which are resulted from initial points selections, thus a better clustering quality can be obtained. The experimental results also show that the F-measure of the improved K-means algorithm has been greatly improved and the clustering results are more stable.
