Abstract
In this study, a new procedure to determine the optimum dimensions for a rectangular collar to minimize the temporal trend of scouring around a pier model is proposed. Unlike previous methods of predicting collar dimensions around a bridge pier, the proposed approach concerns the selection of different collar dimension sizes around a bridge scour in terms of the flume's upstream (Luc/D), downstream (Ldc/D) and width (Lw/D) of the flume. The projected determination method involves utilizing Expert Multi Agent System (E-MAS) based Support Vector Regression (SVR) agents with respect to cooperative-based expert SVR (Co-ESVR). The SVR agents (i.e. SVRLuc, SVRLdc and SVRLw) are set around a rectangular collar to predict the collar dimensions around a bridge pier. In the first layer, the Expert System (ES) is adopted to gather suitable data and send it to the next layer. The multi agent-based SVR adjusts its parameters to find the optimal cost prediction function in the collar dimensions around the bridge pier to reduce the collar around the bridge scour. The weighted sharing strategy was utilized to select the cost optimization function through the root mean square error (RMSE). The efficiency of the proposed optimization method (Co-ESVR) was explored by comparing its outcomes with experimental results. Numerical results indicate that the Co-ESVR achieves better accuracy in reducing the percentage of scour depth (re) with a smaller network size, compared to the non-cooperative approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 172-184 |
| Number of pages | 13 |
| Journal | Neurocomputing |
| Volume | 140 |
| DOIs | |
| Publication status | Published - 22 Sep 2014 |
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A cooperative expert based support vector regression (Co-ESVR) system to determine collar dimensions around bridge pier. / Jahangirzadeh, Afshin; Shamshirband, Shahaboddin; Aghabozorgi, Saeed; Akib, Shatirah; Basser, Hossein; Anuar, Nor Badrul; Kiah, Miss Laiha Mat.
In: Neurocomputing, Vol. 140, 22.09.2014, p. 172-184.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - A cooperative expert based support vector regression (Co-ESVR) system to determine collar dimensions around bridge pier
AU - Jahangirzadeh, Afshin
AU - Shamshirband, Shahaboddin
AU - Aghabozorgi, Saeed
AU - Akib, Shatirah
AU - Basser, Hossein
AU - Anuar, Nor Badrul
AU - Kiah, Miss Laiha Mat
PY - 2014/9/22
Y1 - 2014/9/22
N2 - In this study, a new procedure to determine the optimum dimensions for a rectangular collar to minimize the temporal trend of scouring around a pier model is proposed. Unlike previous methods of predicting collar dimensions around a bridge pier, the proposed approach concerns the selection of different collar dimension sizes around a bridge scour in terms of the flume's upstream (Luc/D), downstream (Ldc/D) and width (Lw/D) of the flume. The projected determination method involves utilizing Expert Multi Agent System (E-MAS) based Support Vector Regression (SVR) agents with respect to cooperative-based expert SVR (Co-ESVR). The SVR agents (i.e. SVRLuc, SVRLdc and SVRLw) are set around a rectangular collar to predict the collar dimensions around a bridge pier. In the first layer, the Expert System (ES) is adopted to gather suitable data and send it to the next layer. The multi agent-based SVR adjusts its parameters to find the optimal cost prediction function in the collar dimensions around the bridge pier to reduce the collar around the bridge scour. The weighted sharing strategy was utilized to select the cost optimization function through the root mean square error (RMSE). The efficiency of the proposed optimization method (Co-ESVR) was explored by comparing its outcomes with experimental results. Numerical results indicate that the Co-ESVR achieves better accuracy in reducing the percentage of scour depth (re) with a smaller network size, compared to the non-cooperative approaches.
AB - In this study, a new procedure to determine the optimum dimensions for a rectangular collar to minimize the temporal trend of scouring around a pier model is proposed. Unlike previous methods of predicting collar dimensions around a bridge pier, the proposed approach concerns the selection of different collar dimension sizes around a bridge scour in terms of the flume's upstream (Luc/D), downstream (Ldc/D) and width (Lw/D) of the flume. The projected determination method involves utilizing Expert Multi Agent System (E-MAS) based Support Vector Regression (SVR) agents with respect to cooperative-based expert SVR (Co-ESVR). The SVR agents (i.e. SVRLuc, SVRLdc and SVRLw) are set around a rectangular collar to predict the collar dimensions around a bridge pier. In the first layer, the Expert System (ES) is adopted to gather suitable data and send it to the next layer. The multi agent-based SVR adjusts its parameters to find the optimal cost prediction function in the collar dimensions around the bridge pier to reduce the collar around the bridge scour. The weighted sharing strategy was utilized to select the cost optimization function through the root mean square error (RMSE). The efficiency of the proposed optimization method (Co-ESVR) was explored by comparing its outcomes with experimental results. Numerical results indicate that the Co-ESVR achieves better accuracy in reducing the percentage of scour depth (re) with a smaller network size, compared to the non-cooperative approaches.
UR - http://www.scopus.com/inward/record.url?scp=84901360343&partnerID=8YFLogxK
U2 - 10.1016/j.neucom.2014.03.024
DO - 10.1016/j.neucom.2014.03.024
M3 - Article
VL - 140
SP - 172
EP - 184
JO - Neurocomputing
JF - Neurocomputing
SN - 0925-2312
ER -