The Experts below are selected from a list of 7176 Experts worldwide ranked by ideXlab platform
Li Xu - One of the best experts on this subject based on the ideXlab platform.
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Research on microblog Filtering Technology based on improved online support vector machine model
2016 IEEE International Conference on Mechatronics and Automation, 2016Co-Authors: Hui Ning, Song Li, Fanhu Zeng, Li XuAbstract:With the rapid growth of the number of micro-blog, a lot of useless information flooded in the users vision, the users find it difficult to choose micro-blog recommendation service according to personal interest, so micro-blog Filtering Technology is applied to the micro-blog service. The interests of users change with the time, so the traditional batch learning can not be able to satisfy the need of users interest model. However, the machine learning which is based on online learning solved these problem in a certain way. The optimization of micro-blog Filtering can decrease classification errors and improve the classification of data, but it has its own disadvantages. Although online support vector machine filtration is excellent, there's long-running shortcomings. The paper focus on the improvement of efficiency of the online support vector machine Filtering by reducing the size of the training set, the number of training and the number of iterations. The experimental results show that the Filtering performance fluctuate slightly, but it can almost be ignored because of the advantage of its efficiency, and the great amount of data is, the greater the efficiency becomes more obvious.
Li Yong - One of the best experts on this subject based on the ideXlab platform.
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Analysis of application experience of inductive Filtering Technology in industrial power system
Electric power automation equipment, 2020Co-Authors: Li Yong, Tu DortmundAbstract:The application experience of inductive Filtering Technology in industrial power system is analyzed.The single-phase equivalent circuit of inductive Filtering,as well as its basic principle and technical characteristics,is introduced and its merits are analyzed.The power circuit topology of primary equipments of an operating industrial power system is shown with main technical parameters and technical characteristics.A detailed field test of power quality of industrial power system is carried out and the results indicate that,the industrial power system applying inductive Filtering Technology suppresses the harmonic currents at system side and decreases the AC magnetic flux of rectifier transformer core.Consequently,the additional harmonic loss of rectifier transformer is reduced,the power factor is enhanced and the power quality is improved.
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ISPACS - Application of inductive Filtering Technology in industrial rectifier power system
2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2017Co-Authors: Shao Pengfei, Li YongAbstract:Application of inductive Filtering Technology in industrial rectifier power system is studied in this paper. Firstly, the single phase equivalent circuit of inductive Filtering and its basic principle is introduced; then, the power circuit topological of primary equipment is proposed, which is designed for an industrial rectifier power system; finally, a detailed field-test is taken, and the test results indicate that the industrial rectifier power system that adopted inductive Filtering Technology not only can effectively suppress the harmonic of industrial custom power system, but also decreases the magnetic flux of rectifier transformer. Consequently, the additional harmonic loss of rectifier transformer is reduced significant which lead to the energy consumption reduction in system range.
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Application of inductive Filtering Technology in industrial rectifier power system
2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2017Co-Authors: Shao Peng-fei, Chen Hao, Li YongAbstract:Application of inductive Filtering Technology in industrial rectifier power system is studied in this paper. Firstly, the single phase equivalent circuit of inductive Filtering and its basic principle is introduced; then, the power circuit topological of primary equipment is proposed, which is designed for an industrial rectifier power system; finally, a detailed field-test is taken, and the test results indicate that the industrial rectifier power system that adopted inductive Filtering Technology not only can effectively suppress the harmonic of industrial custom power system, but also decreases the magnetic flux of rectifier transformer. Consequently, the additional harmonic loss of rectifier transformer is reduced significant which lead to the energy consumption reduction in system range.
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Application prospect of a new transformer inductive Filtering Technology
2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 2008Co-Authors: Shao Pengfei, Li Yong, Luo Longfu, Xu Jiazhu, He Dajiang, Liu FushengAbstract:Different from passive and reactive Filtering methods, this paper proposes a new transformer inductive Filtering Technology. Its characteristics is that it develops the potential electromagnetism capability of the transformer and makes use of the ampere-turn balance action of the interior coupling winding, which can suppress the harmonics in the secondary winding and avoid the harmonics flowing into the primary winding. In addition, it can effectively abate the negative effect of the harmonic magnetic potential on the transformer. This paper introduces three types of new supply transformers, expounds the interrelation and combined technical characteristics, then expands on its research progress and the industrialization condition. Furthermore, the paper summarizes the practical significance of new inductive Filtering Technology and its application prospect. The author adopts systematic analysis method, and carries out systematic research for the transformer inductive Filtering Technology. By means of various model experiments analysis, it verifies the good Filtering influence that the new inductive Filtering Technology has.
Hui Ning - One of the best experts on this subject based on the ideXlab platform.
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Research on microblog Filtering Technology based on improved online support vector machine model
2016 IEEE International Conference on Mechatronics and Automation, 2016Co-Authors: Hui Ning, Song Li, Fanhu Zeng, Li XuAbstract:With the rapid growth of the number of micro-blog, a lot of useless information flooded in the users vision, the users find it difficult to choose micro-blog recommendation service according to personal interest, so micro-blog Filtering Technology is applied to the micro-blog service. The interests of users change with the time, so the traditional batch learning can not be able to satisfy the need of users interest model. However, the machine learning which is based on online learning solved these problem in a certain way. The optimization of micro-blog Filtering can decrease classification errors and improve the classification of data, but it has its own disadvantages. Although online support vector machine filtration is excellent, there's long-running shortcomings. The paper focus on the improvement of efficiency of the online support vector machine Filtering by reducing the size of the training set, the number of training and the number of iterations. The experimental results show that the Filtering performance fluctuate slightly, but it can almost be ignored because of the advantage of its efficiency, and the great amount of data is, the greater the efficiency becomes more obvious.
Song Li - One of the best experts on this subject based on the ideXlab platform.
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Research on microblog Filtering Technology based on improved online support vector machine model
2016 IEEE International Conference on Mechatronics and Automation, 2016Co-Authors: Hui Ning, Song Li, Fanhu Zeng, Li XuAbstract:With the rapid growth of the number of micro-blog, a lot of useless information flooded in the users vision, the users find it difficult to choose micro-blog recommendation service according to personal interest, so micro-blog Filtering Technology is applied to the micro-blog service. The interests of users change with the time, so the traditional batch learning can not be able to satisfy the need of users interest model. However, the machine learning which is based on online learning solved these problem in a certain way. The optimization of micro-blog Filtering can decrease classification errors and improve the classification of data, but it has its own disadvantages. Although online support vector machine filtration is excellent, there's long-running shortcomings. The paper focus on the improvement of efficiency of the online support vector machine Filtering by reducing the size of the training set, the number of training and the number of iterations. The experimental results show that the Filtering performance fluctuate slightly, but it can almost be ignored because of the advantage of its efficiency, and the great amount of data is, the greater the efficiency becomes more obvious.
Fanhu Zeng - One of the best experts on this subject based on the ideXlab platform.
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Research on microblog Filtering Technology based on improved online support vector machine model
2016 IEEE International Conference on Mechatronics and Automation, 2016Co-Authors: Hui Ning, Song Li, Fanhu Zeng, Li XuAbstract:With the rapid growth of the number of micro-blog, a lot of useless information flooded in the users vision, the users find it difficult to choose micro-blog recommendation service according to personal interest, so micro-blog Filtering Technology is applied to the micro-blog service. The interests of users change with the time, so the traditional batch learning can not be able to satisfy the need of users interest model. However, the machine learning which is based on online learning solved these problem in a certain way. The optimization of micro-blog Filtering can decrease classification errors and improve the classification of data, but it has its own disadvantages. Although online support vector machine filtration is excellent, there's long-running shortcomings. The paper focus on the improvement of efficiency of the online support vector machine Filtering by reducing the size of the training set, the number of training and the number of iterations. The experimental results show that the Filtering performance fluctuate slightly, but it can almost be ignored because of the advantage of its efficiency, and the great amount of data is, the greater the efficiency becomes more obvious.
