VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh)
One of the most important processes of erosion and sediment transport in streams is the river most complex engineering issues.this process special effects on water quality indices, action suburbs floor and destroyed much damage to the river and also into the development plans Lack of continuity se...
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Kharazmi University
2018-06-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-2760-en.pdf |
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| author | masooume darmani mohammad nohtani haydeh ara Ali golkarian Salman Sharif Azari |
| author_facet | masooume darmani mohammad nohtani haydeh ara Ali golkarian Salman Sharif Azari |
| author_sort | masooume darmani |
| collection | DOAJ |
| description | One of the most important processes of erosion and sediment transport in streams is the river most complex engineering issues.this process special effects on water quality indices, action suburbs floor and destroyed much damage to the river and also into the development plans Lack of continuity sediment sampling and measurement of many existing stations. due to the low number of hydrometric stations in Iran and the lack of continuity of sediment sampling and measuring in many existing stations, on one hand the exact amount of sediment load in many rivers in the country is not available and because of differences in climatic, hydrological and topographical conditions in the country, on the other hand, the preparation and calibration of sediment Erosion Models different regions, is unavoidableCalibration models of erosion and sedimentation in different locations is difficult and requires financial capital andthe time . the But evolutionary optimization algorithm able to resolve this problems of mathematical and experimental methods in this paper, a new optimization algorithm spiders can be made to education And the evolutionary pattern for input (discharge and precipitation) and rain-gauge gauging stations and Watershed Kardeh designated evolutionary algorithms and artificial network performance for 24 year 24-year dam catchment Kardeh for the period studied. In conclusion, the results proved that social spiders optimization algorithm t better resultspredic to for sediment in watershed Kardeh |
| format | Article |
| id | doaj-art-bda5d589616e49b2b1d89608385c8b1c |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2018-06-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-bda5d589616e49b2b1d89608385c8b1c2025-01-31T17:25:06ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382018-06-011851183198VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh)masooume darmani0mohammad nohtani1haydeh ara2Ali golkarian3Salman Sharif Azari4 PhD student Desertification, Faculty of Desert Studies, Semnan University, iran Assistant Professor of Arid region management department, Faculty of Desert Studies, Semnan University , iran. Assistant Professor of Arid region management department, Faculty of Desert Studies, Semnan University , iran. Assistant Professor, Department of Range and Watershed Management, Faculty of Natural Resources and Environment, Ferdowsi University Of Mashhad (FUM) , iran. Master of Water Resources Management, iran. One of the most important processes of erosion and sediment transport in streams is the river most complex engineering issues.this process special effects on water quality indices, action suburbs floor and destroyed much damage to the river and also into the development plans Lack of continuity sediment sampling and measurement of many existing stations. due to the low number of hydrometric stations in Iran and the lack of continuity of sediment sampling and measuring in many existing stations, on one hand the exact amount of sediment load in many rivers in the country is not available and because of differences in climatic, hydrological and topographical conditions in the country, on the other hand, the preparation and calibration of sediment Erosion Models different regions, is unavoidableCalibration models of erosion and sedimentation in different locations is difficult and requires financial capital andthe time . the But evolutionary optimization algorithm able to resolve this problems of mathematical and experimental methods in this paper, a new optimization algorithm spiders can be made to education And the evolutionary pattern for input (discharge and precipitation) and rain-gauge gauging stations and Watershed Kardeh designated evolutionary algorithms and artificial network performance for 24 year 24-year dam catchment Kardeh for the period studied. In conclusion, the results proved that social spiders optimization algorithm t better resultspredic to for sediment in watershed Kardehhttp://jgs.khu.ac.ir/article-1-2760-en.pdfkeywords: suspended sedimentdam catchment kardehsocial spider evolutionary algorithmnetwork mlpsedimentation |
| spellingShingle | masooume darmani mohammad nohtani haydeh ara Ali golkarian Salman Sharif Azari VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh) تحقیقات کاربردی علوم جغرافیایی keywords: suspended sediment dam catchment kardeh social spider evolutionary algorithm network mlp sedimentation |
| title | VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh) |
| title_full | VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh) |
| title_fullStr | VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh) |
| title_full_unstemmed | VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh) |
| title_short | VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh) |
| title_sort | vmlp neural network design using optimization algorithms to predict spider suspend case study watershed dam kardeh |
| topic | keywords: suspended sediment dam catchment kardeh social spider evolutionary algorithm network mlp sedimentation |
| url | http://jgs.khu.ac.ir/article-1-2760-en.pdf |
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