PMID- 38423611
OWN - NLM
STAT- MEDLINE
DCOM- 20240304
LR  - 20240304
IS  - 0273-1223 (Print)
IS  - 0273-1223 (Linking)
VI  - 89
IP  - 4
DP  - 2024 Feb
TI  - Approximation in scour depth around spur dikes using novel hybrid ensemble 
      data-driven model.
PG  - 962-975
LID - 10.2166/wst.2024.025 [doi]
AB  - The scouring process near spur dikes poses a threat to riverbank stability, 
      making it crucial for river engineering to accurately calculate the maximum scour 
      depth. However, determining the maximum scour depth has been challenging due to 
      the intricacy of scour phenomena surrounding these structures. This research 
      introduces a reliable ensemble data-driven model by hybridizing random tree (RT) 
      using additive regression (AR), bagging (B), and random subspace (RSS) for 
      predicting scour depths around spur dikes. A database of 154 experimental 
      observations was collected from literature, with 103 and 51 observations used for 
      training and testing subsets, respectively. A dimensionless analysis was 
      performed on the collected dataset, selecting four variables as input variables 
      (v/v(s), y/l, l/d(50), and Fd(50)) and d(s)/l as response variables. The 
      performance comparison demonstrates that B_AR_RT has a better coefficient of 
      determination (R(2)) of 0.9693, root mean square error (RMSE) of 0.1305, and 
      Nash-Sutcliffe efficiency (NSE) of 0.9692. Finally, a comparison of the best 
      hybrid model has been done with previous studies, and sensitivity analysis is 
      performed to determine the most influential parameter for predicting the scour 
      depth around spur dikes.
FAU - Singh, Balraj
AU  - Singh B
AD  - Civil Engineering Department, Delhi Technological University, Delhi 110042, India 
      E-mail: balrajsingh_2k21phdce12@dtu.ac.in.
FAU - Minocha, Vijay K
AU  - Minocha VK
AD  - Civil Engineering Department, Delhi Technological University, Delhi 110042, 
      India.
LA  - eng
PT  - Journal Article
PL  - England
TA  - Water Sci Technol
JT  - Water science and technology : a journal of the International Association on 
      Water Pollution Research
JID - 9879497
SB  - IM
MH  - *Rivers
EDAT- 2024/03/01 01:22
MHDA- 2024/03/04 06:47
CRDT- 2024/02/29 20:53
PHST- 2024/03/04 06:47 [medline]
PHST- 2024/03/01 01:22 [pubmed]
PHST- 2024/02/29 20:53 [entrez]
AID - 10.2166/wst.2024.025 [doi]
PST - ppublish
SO  - Water Sci Technol. 2024 Feb;89(4):962-975. doi: 10.2166/wst.2024.025.