Prediction of China’s Express Business Volume Based on FGM (1, 1) Model
With the continuous development of the economy, people’s lifestyle has changed greatly, online shopping has become a better choice for many people, and the express business volume is also increasing. Forecasting express business volume is of benefit to the healthy development of the logistics indust...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/8585238 |
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| _version_ | 1832560525961068544 |
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| author | Chunyan Xiong Liusan Wu |
| author_facet | Chunyan Xiong Liusan Wu |
| author_sort | Chunyan Xiong |
| collection | DOAJ |
| description | With the continuous development of the economy, people’s lifestyle has changed greatly, online shopping has become a better choice for many people, and the express business volume is also increasing. Forecasting express business volume is of benefit to the healthy development of the logistics industry. Based on the data of China’s express business volume from 2015 to 2019, this paper uses the improved Particle Swarm Optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and forecasts China’s express business volume from 2020 to 2023. The results indicate that in the next few years, China’s express business volume will show a large growth trend, indicating that the express delivery industry still has a lot of room for development. |
| format | Article |
| id | doaj-art-6db41176b0e549e692a241207856d463 |
| institution | Kabale University |
| issn | 2314-4629 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-6db41176b0e549e692a241207856d4632025-02-03T01:27:22ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/85852388585238Prediction of China’s Express Business Volume Based on FGM (1, 1) ModelChunyan Xiong0Liusan Wu1College of Information Management, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Information Management, Nanjing Agricultural University, Nanjing 210031, ChinaWith the continuous development of the economy, people’s lifestyle has changed greatly, online shopping has become a better choice for many people, and the express business volume is also increasing. Forecasting express business volume is of benefit to the healthy development of the logistics industry. Based on the data of China’s express business volume from 2015 to 2019, this paper uses the improved Particle Swarm Optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and forecasts China’s express business volume from 2020 to 2023. The results indicate that in the next few years, China’s express business volume will show a large growth trend, indicating that the express delivery industry still has a lot of room for development.http://dx.doi.org/10.1155/2021/8585238 |
| spellingShingle | Chunyan Xiong Liusan Wu Prediction of China’s Express Business Volume Based on FGM (1, 1) Model Journal of Mathematics |
| title | Prediction of China’s Express Business Volume Based on FGM (1, 1) Model |
| title_full | Prediction of China’s Express Business Volume Based on FGM (1, 1) Model |
| title_fullStr | Prediction of China’s Express Business Volume Based on FGM (1, 1) Model |
| title_full_unstemmed | Prediction of China’s Express Business Volume Based on FGM (1, 1) Model |
| title_short | Prediction of China’s Express Business Volume Based on FGM (1, 1) Model |
| title_sort | prediction of china s express business volume based on fgm 1 1 model |
| url | http://dx.doi.org/10.1155/2021/8585238 |
| work_keys_str_mv | AT chunyanxiong predictionofchinasexpressbusinessvolumebasedonfgm11model AT liusanwu predictionofchinasexpressbusinessvolumebasedonfgm11model |