Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper, we propose a user participation behavior prediction model for social hotspots, based on user ...Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper, we propose a user participation behavior prediction model for social hotspots, based on user behavior and relationship data, to predict user participation behavior and topic development trends. Firstly, for the complex factors of user behavior, three dynamic influence factor functions are defined, including individual, peer and community influence. These functions take timeliness into account using a time discretization method. Secondly, to determine laws of individual behavior and group behavior within a social topic, a hotspot user participation behavior prediction model is proposed and associated with the basic concepts of randora field and Markov property in information diffusion. The experimental results show that the model can not only dynamically predict the individual behavior, but also grasp the development trends of topics.展开更多
Based on catastrophe theory,we used the catastrophe progression method to predict the risk of coal and gas outbursts in coal mines.According to the major factors affecting coal and gas outbursts,we built a comprehensi...Based on catastrophe theory,we used the catastrophe progression method to predict the risk of coal and gas outbursts in coal mines.According to the major factors affecting coal and gas outbursts,we built a comprehensive evaluation index system and a coal and gas outburst prediction model.In addition,we performed a standard transformation for each index system;based on the degree the various indices affect the risk of an outburst,to make the data dimensionless.Based on the outburst data from eight mines,we determined catastrophe progression values and verified these values.The results show that:1) converting multi-dimensional problems into one-dimensional problems using this catastrophe progression method can simplify the steps of predicting coal and gas outbursts;2) when pre-determined catastrophe progression values are used to predict coal and gas outbursts,the predicting accuracy rate can be as high as 87.5%;3) the various coal mines have different factors inducing outbursts with varying importance of these factors and 4) the catastrophe progression values,calculated based on these factors,can be used effectively to predict the risk of outbursts in coal mines.展开更多
The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on fiv...The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on five matter-elements,which includedgas pressure,types of coal damage,coal rigidity,initial speed of methane diffusionand in-situ stress.Each index weight was given fairly and quickly through the improvedanalytic hierarchy process,which need not carry on consistency checks,so accuracy ofassessment can be improved.展开更多
基金supported by the National Key Basic Research Program(973 program)of China(No.2013CB329606)National Science Foundation of China(Grant No.61272400)+2 种基金Science and Technology Research Program of the Chongqing Municipal Education Committee(No.KJ1500425)Wen Feng Foundation of CQUPT(No.WF201403)Chongqing Graduate Research And Innovation Project(No.CYS14146)
文摘Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper, we propose a user participation behavior prediction model for social hotspots, based on user behavior and relationship data, to predict user participation behavior and topic development trends. Firstly, for the complex factors of user behavior, three dynamic influence factor functions are defined, including individual, peer and community influence. These functions take timeliness into account using a time discretization method. Secondly, to determine laws of individual behavior and group behavior within a social topic, a hotspot user participation behavior prediction model is proposed and associated with the basic concepts of randora field and Markov property in information diffusion. The experimental results show that the model can not only dynamically predict the individual behavior, but also grasp the development trends of topics.
基金Projects 50574072, 50874089 and 50534049 supported by the National Natural Science Foundation of China08JK366 by the Special Scientific Foundation of Educational Committee of Shaanxi Province
文摘Based on catastrophe theory,we used the catastrophe progression method to predict the risk of coal and gas outbursts in coal mines.According to the major factors affecting coal and gas outbursts,we built a comprehensive evaluation index system and a coal and gas outburst prediction model.In addition,we performed a standard transformation for each index system;based on the degree the various indices affect the risk of an outburst,to make the data dimensionless.Based on the outburst data from eight mines,we determined catastrophe progression values and verified these values.The results show that:1) converting multi-dimensional problems into one-dimensional problems using this catastrophe progression method can simplify the steps of predicting coal and gas outbursts;2) when pre-determined catastrophe progression values are used to predict coal and gas outbursts,the predicting accuracy rate can be as high as 87.5%;3) the various coal mines have different factors inducing outbursts with varying importance of these factors and 4) the catastrophe progression values,calculated based on these factors,can be used effectively to predict the risk of outbursts in coal mines.
基金Supported by the National Natural Science Foundation of China(50534080)the Science and Technology Research Project of Chongqing(CSCT,2006AA7002)
文摘The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on five matter-elements,which includedgas pressure,types of coal damage,coal rigidity,initial speed of methane diffusionand in-situ stress.Each index weight was given fairly and quickly through the improvedanalytic hierarchy process,which need not carry on consistency checks,so accuracy ofassessment can be improved.
