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Search recommendation model based on user search behavior and gradual forgetting collaborative filtering strategy 被引量:3
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作者 LIU Chuan-chang State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2010年第3期110-117,共8页
The existing search engines are lack of the consideration of personalization and display the same search results for different users despite their differences in interesting and purpose. By analyzing user's dynamic s... The existing search engines are lack of the consideration of personalization and display the same search results for different users despite their differences in interesting and purpose. By analyzing user's dynamic search behavior, the paper introduces a new method of using a keyword query graph to express user's dynamic search behavior, and uses Bayesian network to construct the prior probability of keyword selection and the migration probability between keywords for each user. To reflect the dynamic changes of the user's preference, the paper introduces non-lineal gradual forgetting collaborative filtering strategy into the personalized search recommendation model. By calculating the similarity between each two users, the model can do the recommendation based on neighbors and be used to construct the personalized search engine. 展开更多
关键词 search recommendation model search behavior expression keyword query graph gradual forgetting collaborative filtering
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Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy 被引量:23
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作者 Canbing LI Liwu XIAO +4 位作者 Yijia CAO Qianlong ZHU Baling FANG Yi TAN Long ZENG 《Journal of Modern Power Systems and Clean Energy》 SCIE EI 2014年第2期173-180,共8页
Flexible AC transmission systems(FACTS)devices can effectively optimize the distribution of power flow.Power flow entropy can be applied as a measure of load distribution.In this paper,a method is proposed to optimize... Flexible AC transmission systems(FACTS)devices can effectively optimize the distribution of power flow.Power flow entropy can be applied as a measure of load distribution.In this paper,a method is proposed to optimize the distribution of power flow with the coordination of multi-type FACTS devices and establishes the corresponding mathematical models.The modified group searcher optimization(GSO)algorithm is proposed,in which the angle search is combined with chaotic search model to avoid jumping into local optimization.Compared with the different optimal allocation of multi-FACTS devices,the optimal allocation of multi-FACTS devices is achieved under the economic constraints.The locations obtained by this method can achieve the purpose of balancing power flow and enhancing the system performances.The simulations are demonstrated in an IEEE 118-bus power system with two classical types of FACTS,namely static var compensator(SVC)and thyristor controlled series Compensator(TCSC).The simulation results show that the proposed method is feasible and effective. 展开更多
关键词 Chaotic search model Flexible AC transmission system(FACTS) Group searcher optimization(GSO) Power flow entropy
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