Research Article
Demand Forecasting for Rural E-Commerce Logistics: A Gray Prediction Model Based on Weakening Buffer Operator
Table 1
Raw data of logistics demand indicators from 2013 to 2017.
| | Indicator year | X0 (unit: yuan) | X1 (unit: 100 million yuan) | X2 (unit: 10 thousand tons) | X3 (unit: 10 thousand tons) | X4 (unit: 10 thousand tons) | X5 (unit: kilometers) |
| | 2011 | 9371.7 | 336.36 | 1306.95 | 11.41 | 234978 | 190724 | | 2012 | 10542.8 | 11.34 | 1396.33 | 11.39 | 266359 | 194943 | | 2013 | 11067.8 | 262.35 | 1315.90 | 11.01 | 328138 | 202915 | | 2014 | 12245.6 | 374.32 | 1357.34 | 11.27 | 353732 | 212094 | | 2015 | 13360.4 | 351.24 | 1358.13 | 11.38 | 349832 | 216023 | | 2016 | 14512.2 | 423.77 | 1360.22 | 11.37 | 377645 | 218085 | | 2017 | 15779.7 | 455.49 | 1208.56 | 10.43 | 392381 | 219580 |
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