Tunneling-induced ground movement and building damage prediction using hybrid artificial neural networks
The construction of tunnels in urban areas may cause ground displacement which distort and damage overlying buildings and services. Hence, it is a major concern to estimate tunneling-induced ground movements as well as to assess the building damage. Artificial neural networks (ANN), as flexible non-...
| 第一著者: | |
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| フォーマット: | 学位論文 |
| 言語: | 英語 |
| 出版事項: |
2013
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/37932/1/MohsenHajihassaniPFKA2013.pdf |