مدل‌سازی تنش خاک در سدهای خاکی با روش‌های هوش مصنوعی و تعیین ویژگی‌های موثر

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران. .

چکیده

هدف کلی این مقاله انتخاب ویژگی‌های موثر و مدل‌سازی تنش خاک در سدهای خاکی در زمان ساخت با شبکه عصبی به کمک یک الگوریتم بهینه‌ساز و در ادامه نتایج مدل هیبریدی با روش‌های مرسومANFIS  وGEP  مقایسه شده است. پنج ویژگی شامل تراز خاکریزی، زمان ساخت سد، تراز مخزن (آبگیری)، سرعت آبگیری و سرعت خاکریزی به عنوان ورودی‌های مدل هیبریدی انتخاب شده است. با اجرای الگوریتم هیبریدی و تحلیل حساسیت و روش انتخاب ویژگی، تراز خاکریزی و زمان ساخت سد، مؤثرترین ویژگی‌ها در مدل‌سازی تنش کل در سلول‌های منتخب بودند؛ زیرا ترکیب دوتایی شامل تراز‌ خاکریزی و زمان ساخت در سلول‌های TPC25.1 و TPC25.3 و TPC25.4 به ترتیب با مقادیر خطا (MSE) برابر 1/523، 2/747 و 0/750 موثرترین ویژگی‌ها در این سلول‌ها بودند. در سلول TPC25.2 انتخاب سه ویژگی تراز خاکریزی، زمان ساخت و تراز مخزن با توجه به مقدار خطای 5/245 بیش‌ترین تأثیر را در مدل‌سازی تنش کل خاک در این سلول داراست. مقایسه بین مدل ANN با ANFIS و GEP نشان داد، هر چند که اختلاف در دقت مدل‌ها بسیار ناچیز است، می‌توان گفت هر سه مدل جواب قابل ‌قبول و نزدیک به هم داشته‌اند. هم‌چنین نتایج نشان می‌دهد که هر چه پراکندگی داده‌های ورودی مدل بیشتر باشد، مدل استنتاج عصبی- فازی تطبیقی دارای توانایی بیشتری در شبیه‌سازی نسبت به دو مدل ANN و GEP است، زیرا در سلول TPC25.4 مدل ANFIS در دوره آزمون با شاخص‌های آماری ، RMSE ، MAEو NS به ترتیب برابر مقادیر 0/9955، 0/0227، 0/0185 و 0/9666 دارای عملکرد بهتری نسبت به دو مدل دیگر است.
 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Simulation of soil stress in earth dams using artificial intelligence models and determination of effective features

نویسندگان [English]

  • Arvand Hakimi Khansar
  • Javad Parsa
  • Ali Hoseinzadeh dalir
  • Jalal Shiri
PhD candidate, Department of Science and Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
چکیده [English]

The general purpose of this paper is to select effective features and model soil stress in earth dams during construction. Five features, including fill level, duration of construction, reservoir level (impoundment), impounding rate and fill rate, were selected as hybrid model inputs. By performing hybrid algorithm and sensitivity analysis and feature selection method, fill level and duration of construction were recognized as the most effective features in modeling the total stress in selected cells, because concurrent mean square error values for the fill level and duration of construction in TPC25.1, TPC25.3 and TPC25.4 cells were 1.523, 2.747 and 0.750, respectively. In TPC25.2 cell, three features including fill level, duration of construction and impoundment level, had the greatest effect in modeling the total soil stress based on the mean square error value of 5.245. Comparison of the results of the ANN model with ANFIS and GEP showed that although the difference in the accuracy of the models is very small, all three models had acceptable results in the test step, the ANFIS model results indicated that the statistical error measures of , RMSE, MAE and NS in TPC25.4 cell were 0.9955, 0.0227, 0.0185 and 0.9666, respectively. It showed that how much the input data are more scattered, the ANFIS model had more capability than ANN and GEP models to simulate the soil stress in the studied earth dam.

کلیدواژه‌ها [English]

  • Earth dam
  • PSO-ANN hybrid algorithm
  • Feature selection
  • ANFIS
  • Soil vertical stress

مراجع

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نشریه مهندسی عمران امیرکبیر
دوره 54، شماره 1
فروردین 1401
صفحه 247-262

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