Research Of Network Group Emergency Early Warning Monitoring Model Based On Cloud Model

As the network interaction entered the era of Web3.0 Web2.0 era, now people on the network interaction is becoming more and more frequent. Thus derived Web3.0 era of network interactive network events or some sudden blindness, and clustering characteristics.Through the network of real time and convenience that makes people can easily get all kinds of information can also be quickly to participate in the social, economic, and political hot topic of discussion, but due to sudden blindness, and cluster network events, once by certain use and guide public opinion, to the individual, collective and social inestimable serious consequences. Timely preventive, therefore, how to prevent the happening of the bad network events and the correct boot is network events subsequent to the current key research topic.Research on network sudden mass incidents, the network of mass incidents from 2007 academic expression appears, the rapid development of the research in our country, has accumulated a lot of valuable experience and important research achievements, at present our country most of the network group events related research to qualitative analysis, quantitative research and model building is less, mainly concentrated in the concept of network events, propagation mode research, evolutionary stages analysis, construction of index system. The existing main methods of study of network community emergency early warning for complex network theory and BP neural network algorithm, etc., in view of the quantitative- qualitative data conversion of the demand of the quantitative research, this article has introduced the cloud model algorithm, and build a network of community emergency early warning surveillance model. In this paper, the research emphasis is mainly the following points:(1) Related concepts and characteritics of network group emergency. In view of the educational world widespread network concept blurred and research problems related to sudden mass incidents defined the scope of the problem, this paper draw the scholars, on the basis of existing research results, from the perspective of social public security, puts forward the concept of a sudden mass incidents, summarized the characteristics of the network group events and the law of development.(2) The construction of network community emergency early warning index system. Explore related index system based on the research status quo, according to the characteristics of the network group emergency excavated the origin and spread of network group events, based on the principles of network group events early warning index system of building, building contains event attention, the proliferation of events risk and degree of three level indicators and nine secondary indexes such as a network of community emergency early warning index system.(3) The construction of network group emergency early warning monitoring model based on cloud model. Into the cloud model, give full play to the cloud model algorithm to deal with the advantage of fuzzy and uncertain problems, to use its quantitative- qualitative data transformation characteristics of key realization technology and cloud model generator, avoid the network group events early warning surveillance appeared breakpoints and blind spots. Based on the five specific case, using this model and BP neural network algorithm, this paper compares and analyzes proves the feasibility and validity of the model.