پیش‌بینی نشست پی‌های سطحی برروی خاک‌های دانه‌ای بااستفاده از برنامه‌نویسی چندعبارتی (MEP)

نوع مقاله : پژوهشی

نویسندگان

دانشکده‌ی فنی، دانشگاه شاهد، تهران.

چکیده

  به‌واسطه‌ی طبیعت ناهمگون خاک‌های غیرچسبنده و پیچیدگی پارامترهای مؤثر در نشست، پیش‌بینی دقیق نشست پی معمولاً با دشواری‌های بسیاری همراه است. این موضوع از گذشته مدنظر پژوهشگران مختلفی بوده‌است و برخی محققان نیز معادلاتی برای پیش‌بینی نشست پی سطحی ارائه کرده‌اند. به‌دلیل عدم دقت کافی این روابط، پژوهشگران از روش‌های جدیدتری از جمله اجزای محدود، تفاضل ‌محدود، محاسبات نرم و... برای پیش‌بینی نشست استفاده می‌کنند. در پژوهش حاضر مدل جدیدی بااستفاده از هوش مصنوعی برای پیش‌بینی نشست ارائه می‌گردد. هدف از توسعه‌ی این‌گونه مدل‌ها ایجاد فرمول‌هایی دقیق‌تر و درصورت امکان ساده‌تر می‌باشد. در این مقاله عملکرد الگوریتم برنامه‌نویسی چندعبارتی (Multi expression programming) برای پیش‌بینی نشست پی‌های سطحی واقع بر خاک دانه‌ای مورد بررسی قرار می‌گیرد و مقادیر به‌دست‌آمده از مدل‌های جدید با دقیق‌ترین مدل‌های قبلی، مقایسه می‌شوند. سپس تحلیل عملکرد، مطالعه‌ی پارامتری، تحلیل حساسیت و ارزیابی ضریب اطمینان انجام می‌گردد. همان‌طور که از نتایج مشخص است، مقایسه بین مدل‌ MEP و دقیق‌ترین مدل‌‌ها شامل ANN، GP، GEP و EPR در ادبیات فنی نشان می‌دهد که مدل پیشنهادی در این مطالعه، با ضریب هم‌بستگی 45/93 درصد عملکرد بهتری نسبت‌به اکثر مدل‌های توسعه‌یافته قبلی دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Settlement Prediction of Shallow Foundations on Granular Soils Using Multi Expression Programming (MEP)

نویسندگان [English]

  • Bahare Farahani
  • Ali Derakhshani
Geotechnics, Shahed University, Tehran, Iran
چکیده [English]

Due to the non-homogeneous nature of cohesionless soils, and the complexity of the parameters related to settlement, generally the exact estimation of the foundation settlement involves many difficulties. This problem has been studied by many researchers and some equations have been proposed for estimating the settlement of shallow foundations. Because of the low accuracy of these equations, researchers are using more modern techniques like finite elements, finite difference, soft computing, and so on, for calculating the settlement. In the current study, a new model is proposed based on artificial intelligence to predict the settlement. The purpose of developing such models is to achieve more accurate and possibly simpler equations. In this paper, the performance of multi expression programming (MEP) method to predict the settlement of shallow foundations on granular soils is evaluated and the values obtained from the developed models are compared with those from the most accurate previous models. Then, the performance analysis, validation, parametric study and sensitivity analysis are performed. As can be seen from the results, the comparison between the MEP model and the most accurate models including ANN, GP, GEP and EPR in the technical literature showed that the model proposed in this study with correlation coefficient of 93.45 percent, performs better than most previously developed models.

کلیدواژه‌ها [English]

  • Prediction of Settlement
  • Shallow foundation
  • Multi Expression Programming
  • Granular soil

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