کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4943055 | 1437619 | 2017 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An improved grey dynamic trend incidence model with application to factors causing smog weather
ترجمه فارسی عنوان
یک مدل بروز پراکندگی روند پراکندگی خاکستری با استفاده از عوامل ایجاد کننده آب و هوای دود
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کلمات کلیدی
بروز خاکستری، رابطه روند تجزیه و تحلیل پویا، پنل اطلاعات، آب و هوای معتدل،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 87, 30 November 2017, Pages 240-251
Journal: Expert Systems with Applications - Volume 87, 30 November 2017, Pages 240-251
نویسندگان
Wang Junjie, Keith W. Hipel, Dang Yaoguo,