Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran)
Artificial Neural Networks (ANN) is a field that combines science, technology, and ancient and modern knowledge. It has demonstrated the ability to resolve complex engineering issues beyond the computational capacity of conventional approaches and classical mathematics. ANN has applications in vario...
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| Format: | Article |
| Language: | English |
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University North
2025-01-01
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| Series: | Tehnički Glasnik |
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| Online Access: | https://hrcak.srce.hr/file/473492 |
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| author | Semko Arefpanah Alireza Sharafi Alireza Gholamian |
| author_facet | Semko Arefpanah Alireza Sharafi Alireza Gholamian |
| author_sort | Semko Arefpanah |
| collection | DOAJ |
| description | Artificial Neural Networks (ANN) is a field that combines science, technology, and ancient and modern knowledge. It has demonstrated the ability to resolve complex engineering issues beyond the computational capacity of conventional approaches and classical mathematics. ANN has applications in various fields, including computer science, engineering science, biology and medical science, and communication science. Neural networks are particularly useful in civil engineering, particularly in geotechnical problems, where soil heterogeneity and nonlinear behavior significantly impact geotechnical phenomena. Researchers have employed ANN to address various geotechnical engineering issues, including behavioral modeling, due to their potent abilities on nonlinear and multivariate problems. In this study, information from boreholes was used to collect and classify data to describe soil strata. The outputs of the neural network showed general consistency when compared to experimental borehole data, indicating its effectiveness in estimating changes in the soil layer. This was achieved by first presenting the network with information from various boreholes. |
| format | Article |
| id | doaj-art-e2c87788ca8848f8bd19f3a6ee4f30ce |
| institution | Kabale University |
| issn | 1846-6168 1848-5588 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | University North |
| record_format | Article |
| series | Tehnički Glasnik |
| spelling | doaj-art-e2c87788ca8848f8bd19f3a6ee4f30ce2025-02-06T15:55:57ZengUniversity NorthTehnički Glasnik1846-61681848-55882025-01-0119114915610.31803/tg-20220914012010Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran)Semko Arefpanah0Alireza Sharafi1Alireza Gholamian2Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Civil Engineering, Islamic Azad University, Hamadan Branch, IranArtificial Neural Networks (ANN) is a field that combines science, technology, and ancient and modern knowledge. It has demonstrated the ability to resolve complex engineering issues beyond the computational capacity of conventional approaches and classical mathematics. ANN has applications in various fields, including computer science, engineering science, biology and medical science, and communication science. Neural networks are particularly useful in civil engineering, particularly in geotechnical problems, where soil heterogeneity and nonlinear behavior significantly impact geotechnical phenomena. Researchers have employed ANN to address various geotechnical engineering issues, including behavioral modeling, due to their potent abilities on nonlinear and multivariate problems. In this study, information from boreholes was used to collect and classify data to describe soil strata. The outputs of the neural network showed general consistency when compared to experimental borehole data, indicating its effectiveness in estimating changes in the soil layer. This was achieved by first presenting the network with information from various boreholes.https://hrcak.srce.hr/file/473492artificial intelligencebehavioral modelbehavioral modelinggeotechnical engineeringliquefaction |
| spellingShingle | Semko Arefpanah Alireza Sharafi Alireza Gholamian Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) Tehnički Glasnik artificial intelligence behavioral model behavioral modeling geotechnical engineering liquefaction |
| title | Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) |
| title_full | Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) |
| title_fullStr | Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) |
| title_full_unstemmed | Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) |
| title_short | Classification of Layers Using Artificial Neural Networks in the Province of Kurdistan (Iran) |
| title_sort | classification of layers using artificial neural networks in the province of kurdistan iran |
| topic | artificial intelligence behavioral model behavioral modeling geotechnical engineering liquefaction |
| url | https://hrcak.srce.hr/file/473492 |
| work_keys_str_mv | AT semkoarefpanah classificationoflayersusingartificialneuralnetworksintheprovinceofkurdistaniran AT alirezasharafi classificationoflayersusingartificialneuralnetworksintheprovinceofkurdistaniran AT alirezagholamian classificationoflayersusingartificialneuralnetworksintheprovinceofkurdistaniran |