An improved grey dynamic trend incidence model with application to factors causing smog weather. (30th November 2017)

• Record Type: Journal Article
• Authors: Wang, Junjie; Hipel, Keith W.; Dang, Yaoguo
• Is Part Of: Expert systems with applications. Volume 87(2017)
• Page Start: 240
• Page End: 251
• Publication Date: 2017-11-30
• Subjects: Grey incidence -- Trend relationship -- Dynamic analysis -- Panel data -- Smog weather; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2017.06.012
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Trigonometric functions are used to measure the degree of the grey trend incidence. Dynamic connections between two data sets can be obtained over each data point. The Periodic fluctuation can be overcome by allowing the length of time t to change. Two Extended Models utilized to the panel data are presented. Abstract: A new grey incidence model, called the grey dynamic trend incidence model GDTIM(t), is designed to broaden the scope of this type of model. In particular, a degree of the grey trend incidence, an array and a matrix of the grey dynamic trend incidence are obtained from two data sets which include both time series and panel data, by using the GDTIM(t) model. The new model includes two parts. One component is a judgment factor which is used to determine whether the trend of two sequences is the same or different. The other part is a measurement factor for calculating the absolute degree of grey trend incidence. Then, the properties of the model GDTIM(t) are discussed. Two extended models based on GDTIM(t), which are utilized for application to panel data, are established. One is for calculating the connection between indicators, and the other one is for different objects. The new model is used to dynamically analyze factors connected to smog weather in south Jiangsu province.