An adaptive location prediction model based on fuzzy control

2011 ◽  
Vol 34 (7) ◽  
pp. 816-834 ◽  
Author(s):  
Theodoros Anagnostopoulos ◽  
Christos Anagnostopoulos ◽  
Stathes Hadjiefthymiades
Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Sijia Chen ◽  
Jian Zhang ◽  
Fanwei Meng ◽  
Dini Wang

User location prediction in location-based social networks can predict the density of people flow well in terms of intelligent transportation, which can make corresponding adjustments in time to make traffic smooth, reduce fuel consumption, reduce greenhouse gas emissions, and help build a green cycle low-carbon transportation green system. This paper proposes a Markov chain position prediction model based on multidimensional correction (MDC-MCM). Firstly, extract corresponding information from the user’s historical check-in position sequence as a position-position conversion map. Secondly, the influence of check-in period, space distance, and other factors on the position prediction is linearly weighted and merged with the position prediction of the n-order Markov chain to construct MDC-MCM. Finally, we conduct a comprehensive performance evaluation of MDC-MCM using the dataset collected from Brightkite. Experimental results show that compared with other advanced location prediction technologies, MDC-MCM achieves better location prediction results.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 10754-10767
Author(s):  
Jiujun Cheng ◽  
Huaichen Yan ◽  
Aiguo Zhou ◽  
Chunmei Liu ◽  
Ding Cheng ◽  
...  

Author(s):  
Yucheng Zhang ◽  
Jinglong Hu ◽  
Jiangtao Dong ◽  
Yao Yuan ◽  
Jihua Zhou ◽  
...  

2014 ◽  
Vol 7 (1) ◽  
pp. 107
Author(s):  
Ilyes Elaissi ◽  
Okba Taouali ◽  
Messaoud Hassani

2011 ◽  
Vol 34 (6) ◽  
pp. 1148-1154 ◽  
Author(s):  
Hui-Yan JIANG ◽  
Mao ZONG ◽  
Xiang-Ying LIU

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