Construction of LNG receiving terminals The scale of receiving terminals is expanding rapidly At the end of 1999,the state approved the Guangdong LNG Pilot Project,which opened the prelude to the construction of LNG r...Construction of LNG receiving terminals The scale of receiving terminals is expanding rapidly At the end of 1999,the state approved the Guangdong LNG Pilot Project,which opened the prelude to the construction of LNG receiving terminals.In 2006,China’s first LNG receiving terminal,namely Dapeng LNG Receiving Terminal in Shenzhen,Guangdong Province,was put into operation,marking the beginning of the use of overseas natural gas in China.Since then,LNG receiving terminals including Shanghai Wuhaogou,Fujian Putian and Shanghai Yangshangang have been put into operation successively.During the“11th Five-year Plan”period,four LNG receiving terminals were built and put into operation,with a total receiving capacity of 9.8 million tons/year.Construction entered its peak period during the“12th Five-year Plan”period.Ten LNG receiving terminals including Liaoning Dalian,Jiangsu Rudong.展开更多
Identifying influential nodes in complex networks is essential for network robust and stability,such as viral marketing and information control.Various methods have been proposed to define the influence of nodes.In th...Identifying influential nodes in complex networks is essential for network robust and stability,such as viral marketing and information control.Various methods have been proposed to define the influence of nodes.In this paper,we comprehensively consider the global position and local structure to identify influential nodes.The number of iterations in the process of k-shell decomposition is taken into consideration,and the improved k-shell decomposition is then put forward.The improved k-shell decomposition and degree of target node are taken as the benchmark centrality,in addition,as is well known,the effect between node pairs is inversely proportional to the shortest path length between two nodes,and then we also consider the effect of neighbors on target node.To evaluate the performance of the proposed method,susceptible-infected(SI)model is adopted to simulate the spreading process in four real networks,and the experimental results show that the proposed method has obvious advantages over classical centrality measures in identifying influential nodes.展开更多
文摘Construction of LNG receiving terminals The scale of receiving terminals is expanding rapidly At the end of 1999,the state approved the Guangdong LNG Pilot Project,which opened the prelude to the construction of LNG receiving terminals.In 2006,China’s first LNG receiving terminal,namely Dapeng LNG Receiving Terminal in Shenzhen,Guangdong Province,was put into operation,marking the beginning of the use of overseas natural gas in China.Since then,LNG receiving terminals including Shanghai Wuhaogou,Fujian Putian and Shanghai Yangshangang have been put into operation successively.During the“11th Five-year Plan”period,four LNG receiving terminals were built and put into operation,with a total receiving capacity of 9.8 million tons/year.Construction entered its peak period during the“12th Five-year Plan”period.Ten LNG receiving terminals including Liaoning Dalian,Jiangsu Rudong.
文摘Identifying influential nodes in complex networks is essential for network robust and stability,such as viral marketing and information control.Various methods have been proposed to define the influence of nodes.In this paper,we comprehensively consider the global position and local structure to identify influential nodes.The number of iterations in the process of k-shell decomposition is taken into consideration,and the improved k-shell decomposition is then put forward.The improved k-shell decomposition and degree of target node are taken as the benchmark centrality,in addition,as is well known,the effect between node pairs is inversely proportional to the shortest path length between two nodes,and then we also consider the effect of neighbors on target node.To evaluate the performance of the proposed method,susceptible-infected(SI)model is adopted to simulate the spreading process in four real networks,and the experimental results show that the proposed method has obvious advantages over classical centrality measures in identifying influential nodes.
