Sediment, scour and fuzzy Logic in maritime structures

سال انتشار: 1393
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 807

فایل این مقاله در 8 صفحه با فرمت PDF و WORD قابل دریافت می باشد

این مقاله در بخشهای موضوعی زیر دسته بندی شده است:

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

MMSCES02_024

تاریخ نمایه سازی: 16 خرداد 1394

چکیده مقاله:

Accurate prediction of longshore transport in the nearshore zone is essential for control of shoreline erosion and beach evolution. Also an accurate estimation of scour depth around structures is important for coastal and ocean engineers in the design of marine structures. Fuzzy logic as a remarkable methodology has been created, implemented and developed by the leading researchers of our time and has been really blossomed. Its utility is fully appreciated by theoreticians and practitioners alike. Not only does it point us in the right research directions, but it also provide the powerful tools ready for building efficient and powerful intelligent systems capable of solving very large-scale, complex system problems and difficult problems, among other things, which contain nonlinearities. This study focuses on how fuzzy logic have been applied by researchers in the field of breakwater designing and surveying. The result show that fuzzy logic has a better predictive performance and less cost than analytical, numerical methods that do not recourse to soft computing. Also fuzzy system and fuzzy neural network models have the advantages of incorporating flexible reasoning as expert systems when compared to hybrid neural networks; however, they require the development of new prediction enhancement techniques for the improvement of their forecast. A close fit is always obtained when fuzzy logic is applied and errors are much less than those of conventional techniques.

نویسندگان

omid nejadkazem

Assistant Professor, Standard Research Institute, Karaj, Iran

roghayeh rezaei

Ph.D. Student, University of Tabriz, Tabriz, Iran

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Bakhtyar, R., Ghaheri, A., Bakhtiary, A. Y., & Baldock, T. ...
  • Bakhtyar, R., Ghaheri, _ Bakhtiary, A. Y., & Jeng, D. ...
  • Balas, C. E., Koc, M. L., & Tur, R. (2010). ...
  • Bateni, S. M., & Jeng, D. S. (2007). Estimation of ...
  • Erdik, T. (2009). Fuzzy logic approach to conventional rubble mound ...
  • Kambekar, A. R., & Deo, M. C. (2003). Estimation of ...
  • Koc, M. L., & Balas, C. E. (2012). Genetic algorithms ...
  • Patil, S. G., Mandal, S., & Hegde, A. _ (2012). ...
  • Ruan, D. (1997). Fuzzy Logic, Neural Networks, and Genetic Algorithms. ...
  • Sivanandam, S. N., Sumathi, S., & Deepa, S. N. (2007). ...
  • نمایش کامل مراجع