River Water Level Prediction in Coastal Catchment using hybridized relevance vector machine model with improved grasshopper optimization

2021 ◽  
pp. 126477
Author(s):  
Hai Tao ◽  
Najah Kadhim Al-Bedyry ◽  
Khaled Mohamed Khedher ◽  
Shamsuddin Shahid ◽  
Zaher Mundher Yaseen
2010 ◽  
Vol 66 (1) ◽  
pp. 93-98
Author(s):  
Toru HIRAOKA ◽  
Masataka IKARI ◽  
Hiromi YUKI

2019 ◽  
Vol 14 (2) ◽  
pp. 260-268 ◽  
Author(s):  
Shuichi Tsuchiya ◽  
◽  
Masaki Kawasaki

With the aim of accurately predicting river water levels a few hours ahead in the event of a flood, we created a river water level prediction model consisting of a runoff model, a channel model, and data assimilation technique. We also developed a cascade assimilation method that allows us to calculate assimilations of water levels observed at multiple points using particle filters in real-time. As a result of applying the river water level prediction model to Arakawa Basin using the assimilation technique, it was confirmed that reproductive simulations that produce results very similar to the observed results could be achieved, and that we would be able to predict river water levels less affected by the predicted amount of rainfall.


Author(s):  
Cristina Vittucci ◽  
Leila Guerriero ◽  
Paolo Ferrazzoli ◽  
Rachid Rahmoune ◽  
Veronica Barraza ◽  
...  

2010 ◽  
Vol 66 (1) ◽  
pp. 99-103
Author(s):  
Toru HIRAOKA ◽  
Masataka IKARI ◽  
Hiromi YUKI

Sign in / Sign up

Export Citation Format

Share Document