Research on Accident Early Warning Model Based on Entropy Weight and Extension Theory

Abstract

The occurrence of accident is influenced by multiple factors, so in the process of accident warning model construction, we should take full account of the relationships between all of the factors and the accident and the roles that these factors played in the accident. This paper constructs an accident warning model by employing the entropy weight and extension theory. On one hand, this model employs entropy weight theory to determine the weights of various factors, which will avoid the subjectivity of weights determination and the complexity of computing. On the other hand, it constructs accident warning classic and partial unit matter-elements with applying extension theory and method, and this step can avoid the possible subjectivity in this evaluation model by using comprehensive correlation degree as evaluation criteria. Finally, take coal and gas outburst accident as an example, the validity of the model is verified from the weights of various factors which cause outburst and outburst risk size. This is a new methodology in the process of accident warning model construction. Keywords-entropy weight; extension theory; early warming model I.978-1-4244-6581-1/11/$26.00 ©2011 IEEE

Study on service selection effort estimation in service oriented architecture‐based applications powered by information entropy weight fuzzy comprehensive evaluation model

“…Common evaluation methods firstly take the weighted average and then calculate the synthesis exponent, such way of data processing of parameters is not considered rational [44]. This method has been presented and positively applied in diverse fields like, information security risk assessment [45] water quality assessment [46], selection of a fit medical information system (MIS) vendor [47], assessment of development of sports [48], information system selection [49], selecting the best facility project [44], assessment of corporate social responsibility [50], satellite selection [51], accident warning model [52], assessment of bank project risk [53], tourism destination evaluation [54], wine quality assessment [55], and supplier selection [56].…”