Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel
Sediment transport is a prevalent vital process in uvial and coastalenvironments, and \incipient motion" is an issue inseparably bound to this topic. Thisstudy utilizes a novel hybrid method based on Group Method of Data Handling (GMDH)and Genetic Algorithm (GA) to...
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| Format: | Article |
| Language: | English |
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Sharif University of Technology
2017
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| Online Access: | http://eprints.usm.my/37853/ http://eprints.usm.my/37853/1/SCI_Volume_24_Issue_3_Pages_1000-1009-pre.pdf |
| _version_ | 1848878306220310528 |
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| author | Ebtehaj, I. Bonakdari, H. Khoshbin, F. Hin, Ch. Joo Bong Ab Ghanid, A. |
| author_facet | Ebtehaj, I. Bonakdari, H. Khoshbin, F. Hin, Ch. Joo Bong Ab Ghanid, A. |
| author_sort | Ebtehaj, I. |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Sediment transport is a prevalent vital process in uvial and coastalenvironments, and \incipient motion" is an issue inseparably bound to this topic. Thisstudy utilizes a novel hybrid method based on Group Method of Data Handling (GMDH)and Genetic Algorithm (GA) to design GMDH structural (GMDH-GA). Also, SingularValue Decomposition (SVD) was utilized to compute the linear coefficient vectors. Inorder to predict the densimetric Froude number (Fr), the ratio of median diameter ofparticle size to hydraulic radius (d=R) and the ratio of sediment deposit thickness tohydraulic radius (ts=R) are utilized as e ective parameters. Using three di erent sources ofexperimental data and GMDH-GA model, a new equation is proposed to predict incipientmotion. The performance of development equation is compared using GMDH-GA andtraditional equations . The results indicate that the presented equation is more accurate(RMSE= 0:18 andMAPE= 6:48%) than traditional methods. Also, a sensitivityanalysis is presented to study the performance of each input combination in predictingincipient motion (15) Development of Group Method of Data Handling based on Genetic Algorithm to predict incipient motion in rigid rectangular storm water channel. |
| first_indexed | 2025-11-15T17:29:14Z |
| format | Article |
| id | usm-37853 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:29:14Z |
| publishDate | 2017 |
| publisher | Sharif University of Technology |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-378532017-12-08T02:15:36Z http://eprints.usm.my/37853/ Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel Ebtehaj, I. Bonakdari, H. Khoshbin, F. Hin, Ch. Joo Bong Ab Ghanid, A. TD429.5-480.7 Water purification. Water treatment and conditioning. Saline water conversion Sediment transport is a prevalent vital process in uvial and coastalenvironments, and \incipient motion" is an issue inseparably bound to this topic. Thisstudy utilizes a novel hybrid method based on Group Method of Data Handling (GMDH)and Genetic Algorithm (GA) to design GMDH structural (GMDH-GA). Also, SingularValue Decomposition (SVD) was utilized to compute the linear coefficient vectors. Inorder to predict the densimetric Froude number (Fr), the ratio of median diameter ofparticle size to hydraulic radius (d=R) and the ratio of sediment deposit thickness tohydraulic radius (ts=R) are utilized as e ective parameters. Using three di erent sources ofexperimental data and GMDH-GA model, a new equation is proposed to predict incipientmotion. The performance of development equation is compared using GMDH-GA andtraditional equations . The results indicate that the presented equation is more accurate(RMSE= 0:18 andMAPE= 6:48%) than traditional methods. Also, a sensitivityanalysis is presented to study the performance of each input combination in predictingincipient motion (15) Development of Group Method of Data Handling based on Genetic Algorithm to predict incipient motion in rigid rectangular storm water channel. Sharif University of Technology 2017 Article PeerReviewed application/pdf en cc_by http://eprints.usm.my/37853/1/SCI_Volume_24_Issue_3_Pages_1000-1009-pre.pdf Ebtehaj, I. and Bonakdari, H. and Khoshbin, F. and Hin, Ch. Joo Bong and Ab Ghanid, A. (2017) Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel. Scientia Iranica, 24 (3). pp. 1000-1009. ISSN 1026-3098 http://scientiairanica.sharif.edu/article_4083_f71e5aa91c3f919a4d3add7cb056cb59.pdf |
| spellingShingle | TD429.5-480.7 Water purification. Water treatment and conditioning. Saline water conversion Ebtehaj, I. Bonakdari, H. Khoshbin, F. Hin, Ch. Joo Bong Ab Ghanid, A. Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel |
| title | Development of group method of data handling based
on genetic algorithm to predict incipient motion in
rigid rectangular storm water channel |
| title_full | Development of group method of data handling based
on genetic algorithm to predict incipient motion in
rigid rectangular storm water channel |
| title_fullStr | Development of group method of data handling based
on genetic algorithm to predict incipient motion in
rigid rectangular storm water channel |
| title_full_unstemmed | Development of group method of data handling based
on genetic algorithm to predict incipient motion in
rigid rectangular storm water channel |
| title_short | Development of group method of data handling based
on genetic algorithm to predict incipient motion in
rigid rectangular storm water channel |
| title_sort | development of group method of data handling based
on genetic algorithm to predict incipient motion in
rigid rectangular storm water channel |
| topic | TD429.5-480.7 Water purification. Water treatment and conditioning. Saline water conversion |
| url | http://eprints.usm.my/37853/ http://eprints.usm.my/37853/ http://eprints.usm.my/37853/1/SCI_Volume_24_Issue_3_Pages_1000-1009-pre.pdf |