Big data flow errors correction model based on Q-learning

2022 ◽  
Vol 9 (1) ◽  
pp. 1-12
Author(s):  
Sidi Mohamed Snineh ◽  
Mohamed Youssfi ◽  
Noureddine El Abid Amrani ◽  
Omar Bouattane
2021 ◽  
pp. 1-17
Author(s):  
Yixu Liu ◽  
Xiushan Lu ◽  
Shuqiang Xue ◽  
Shengli Wang

Abstract The layout of seafloor datum points is the key to constructing the seafloor geodetic datum network, and a reliable underwater positioning model is the prerequisite for achieving precise deployment of the datum points. The traditional average sound speed positioning model is generally adopted in underwater positioning due to its simple and efficient algorithm, but it is sensitive to incident angle related errors, which lead to unreliable positioning results. Based on the relationship between incident angle and sound speed, the sound speed function model considering the incident angle has been established. Results show that the accuracy of positioning is easily affected by errors related to the incident angle; the new average sound speed correction model based on the incident angle proposed in this paper is used to significantly improve the underwater positioning accuracy.


ACS Omega ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 4408-4416
Author(s):  
Jiwon Roh ◽  
Subean Jang ◽  
Suyeun Kim ◽  
Hyungtae Cho ◽  
Junghwan Kim
Keyword(s):  
Big Data ◽  

2019 ◽  
Vol 11 (1) ◽  
pp. 26-35 ◽  
Author(s):  
Zhen Deng ◽  
Haojun Guan ◽  
Rui Huang ◽  
Hongzhuo Liang ◽  
Liwei Zhang ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document