caa a22 4500 605470650 CHVBK 20210128100329.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00500-014-1268-y doi (NATIONALLICENCE)springer-10.1007/s00500-014-1268-y Using fractional order accumulation to reduce errors from inverse accumulated generating operator of grey model [Elektronische Daten] [Lifeng Wu, Sifeng Liu, Ligen Yao, Ruiting Xu, Xunping Lei] To smooth the randomness, a grey forecasting model is formulated using the data of accumulating generation operator (AGO) rather than original data. Then the inverse accumulating generation operator (IAGO) is applied to find the predicted values of original data. It is proved that the errors from IAGO are affected by the order number of AGO. To achieve an accurate prediction, GM(2,1), which stands for one-variable and second-order differential equation, has been improved by means of fractional order AGO. Finally, four real data sets are imported for comparing the performance of the developed GM(2,1) with several other grey models, such as traditional GM(2,1) and GM(1,1). The simulation results show that optimized GM(2,1) has higher performances not only on model fitting but also on forecasting. Springer-Verlag Berlin Heidelberg, 2014 Grey system nationallicence GM(2, 1) model nationallicence Fractional order accumulation nationallicence Tourism demand forecasting nationallicence Deaths in road traffic accidents nationallicence Wu Lifeng College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut Liu Sifeng College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut Yao Ligen School of Economics and Management, Hebei University of Engineering, 056038, Handan, China aut Xu Ruiting College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut Lei Xunping College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut Soft Computing Springer Berlin Heidelberg 19/2(2015-02-01), 483-488 1432-7643 19:2<483 2015 19 500 https://doi.org/10.1007/s00500-014-1268-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1268-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wu Lifeng College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut NATIONALLICENCE 700 1- Liu Sifeng College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut NATIONALLICENCE 700 1- Yao Ligen School of Economics and Management, Hebei University of Engineering, 056038, Handan, China aut NATIONALLICENCE 700 1- Xu Ruiting College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut NATIONALLICENCE 700 1- Lei Xunping College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/2(2015-02-01), 483-488 1432-7643 19:2<483 2015 19 500