To achieve good results in convolutional neural networks(CNN) for text classification task, term-based pooling operation in CNNs is proposed. Firstly, the convolution results of several convolution kernels are combine...To achieve good results in convolutional neural networks(CNN) for text classification task, term-based pooling operation in CNNs is proposed. Firstly, the convolution results of several convolution kernels are combined by this method, and then the results after combination are made pooling operation, three sorts of CNN models(we named TBCNN, MCT-CNN and MMCT-CNN respectively) are constructed and then corresponding algorithmic thought are detailed on this basis. Secondly, relevant experiments and analyses are respectively designed to show the effects of three key parameters(convolution kernel, combination kernel number and word embedding) on three kinds of CNN models and to further demonstrate the effect of the models proposed. The experimental results show that compared with the traditional method of text classification in CNNs, term-based pooling method is addressed that not only the availability of the way is proved, but also the performance shows good superiority.展开更多
In this paper, we propose Term-based Semantic Peerto-Peer Networks （TSPN） to achieve semantic search. For each peer, TSPN builds a full text index of its documents. Through the analysis of resources, TSPN obtains se...In this paper, we propose Term-based Semantic Peerto-Peer Networks （TSPN） to achieve semantic search. For each peer, TSPN builds a full text index of its documents. Through the analysis of resources, TSPN obtains series of terms, and distributes these terms into the network. Thus, TSPN can use query terms to locate appropriate peers to perform semantic search. Moreover, unlike the traditional structured P2P networks, TSPN uses the terms, not the peers, as the logical nodes of DHT. This can withstand the impact of network chum. The experimental results show that TSPN has better performance compared with the existing P2P semantic searching algorithms.展开更多
近年来,建设清洁低碳安全高效的能源体系,发展可再生能源替代,构建以新能源为主体的新型电力系统成为我国能源发展的必然趋势。在风光资源富集地区,随着新能源装机不断增加,大型综合能源基地得到快速发展。该文基于主客观赋权法建立多...近年来,建设清洁低碳安全高效的能源体系,发展可再生能源替代,构建以新能源为主体的新型电力系统成为我国能源发展的必然趋势。在风光资源富集地区,随着新能源装机不断增加,大型综合能源基地得到快速发展。该文基于主客观赋权法建立多能互补综合能源基地评估体系,对我国“三北”、西南及东部沿海区域发展布局多能互补基地进行评估。为进一步提升多能互补基地经济效益,建立基于长短期记忆神经网络(long short term memory,LSTM)的电价预测模型及多能互补日前优化调度模型,利用粒子群优化算法进行寻优,以实现能源基地综合收益最大化的日前优化调度目标。最后,以甘肃陇东千万kW级多能互补综合能源基地为例,分别开展夏季及冬季典型日的优化调度算例仿真,结果表明,该优化调度方法能够促进基地内新能源消纳的同时最大化能源基地综合收益,为大型综合能源基地的日前优化调度提供技术支撑。展开更多
文摘To achieve good results in convolutional neural networks(CNN) for text classification task, term-based pooling operation in CNNs is proposed. Firstly, the convolution results of several convolution kernels are combined by this method, and then the results after combination are made pooling operation, three sorts of CNN models(we named TBCNN, MCT-CNN and MMCT-CNN respectively) are constructed and then corresponding algorithmic thought are detailed on this basis. Secondly, relevant experiments and analyses are respectively designed to show the effects of three key parameters(convolution kernel, combination kernel number and word embedding) on three kinds of CNN models and to further demonstrate the effect of the models proposed. The experimental results show that compared with the traditional method of text classification in CNNs, term-based pooling method is addressed that not only the availability of the way is proved, but also the performance shows good superiority.
基金Supported by the National Natural Science Foundation of China( 60873225, 60773191, 70771043)National High Technology Research and Development Program of China ( 2007AA01Z403)Wuhan Youth Science and Technology Chenguang Program (200950431171)
文摘In this paper, we propose Term-based Semantic Peerto-Peer Networks （TSPN） to achieve semantic search. For each peer, TSPN builds a full text index of its documents. Through the analysis of resources, TSPN obtains series of terms, and distributes these terms into the network. Thus, TSPN can use query terms to locate appropriate peers to perform semantic search. Moreover, unlike the traditional structured P2P networks, TSPN uses the terms, not the peers, as the logical nodes of DHT. This can withstand the impact of network chum. The experimental results show that TSPN has better performance compared with the existing P2P semantic searching algorithms.
文摘近年来,建设清洁低碳安全高效的能源体系,发展可再生能源替代,构建以新能源为主体的新型电力系统成为我国能源发展的必然趋势。在风光资源富集地区,随着新能源装机不断增加,大型综合能源基地得到快速发展。该文基于主客观赋权法建立多能互补综合能源基地评估体系,对我国“三北”、西南及东部沿海区域发展布局多能互补基地进行评估。为进一步提升多能互补基地经济效益,建立基于长短期记忆神经网络(long short term memory,LSTM)的电价预测模型及多能互补日前优化调度模型,利用粒子群优化算法进行寻优,以实现能源基地综合收益最大化的日前优化调度目标。最后,以甘肃陇东千万kW级多能互补综合能源基地为例,分别开展夏季及冬季典型日的优化调度算例仿真,结果表明,该优化调度方法能够促进基地内新能源消纳的同时最大化能源基地综合收益,为大型综合能源基地的日前优化调度提供技术支撑。
