کاربرد ماشین بردار پشتیبان در مدل‌سازی فرونشست زمین در بخش‌هایی از دشت علی‌آباد قم

نوع مقاله : مقاله پژوهشی

نویسندگان

1 زمین شناسی مهندسی دانشگاه تهران

2 گروه زمین شناسی مهندسی، دانشگاه تهران

3 دانشگاه قم، گروه عمران

چکیده

با گسترش شهرنشینی، صنعت و کشاورزی، افزایش دما و کاهش بارندگی، نیاز به تامین منابع آب مورد نیاز افزایش یافته است. استخراج بیش‌از حد آب‌های زیرزمینی به منظور تامیین آب مصرفی، باعث کاهش سطح آب زیرزمینی و بروز فرونشست می‌شود. در این مطالعه، به منظور ساخت مدل فرونشست از رویکرد ماشین بردار پشتیبان، استفاده شده است. افت سطح آب زیرزمینی، ضخامت رسوبات آبرفتی، قابلیت انتقال رسوبات آبرفتی و مدول الاستیسیته به عنوان پارامترهای مستقل مدل‌سازی فرونشست با ماشین بردار پشتیبان مورد استفاده قرار گرفته است. نتایج حاصل از پژوهش نشان داده است که مدل ماشین بردار پشتیبان با دقت خوبی توانسته است فرونشست را مدل‌سازی کند. برای صحت‌سنجی عملکرد ماشین بردار پشتیبان، نتایج حاصل از مدل، با مقادیر اندازه‌گیری شده از روش InSAR حاصل از تصاویر ماهواره‌ای دشت علی‌آباد قم ارزیابی شده است. همچنین به منظور بررسی میزان تاثیرگذاری پارامترهای ورودی مدل بر فرونشست، تحلیل حساسیت انجام گرفته است که نتایج به دست آمده نشان می‌دهد وقوع فرونشست به افت سطح آب زیرزمینی در منطقه وابستگی زیادی دارد. در نهایت با استفاده از داده‌های جدید تعمیم‌پذیری مدل مورد بررسی قرار گرفته و نتایج حاکی از توانایی تعمیم‌پذیری مدل ماشین بردار پشتیبان فرونشست می‌باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Application of support vector machine in modeling land subsidence in parts of Aliabad plain of Qom

نویسندگان [English]

  • Ali M. Rajabi 1
  • yasaman Abolghasemi 2
  • Ali Edalat 3
1 Engineering Geology, university of Tehran
2 Engineering Geology Department, University of Tehran
3 University of Qom
چکیده [English]

Due to the enhancement of urbanization, industry, and agriculture, increasing temperature, and decreasing rainfall, the demand for water supply has increased. Excessive extraction of groundwater for consumption imposes a decline in the groundwater level and the occurrence of subsidence as a consequence. In this study, a support vector machine approach is applied to model the subsidence. Groundwater level drop, the thickness of alluvial sediments, the transmissivity of alluvial sediments, and elasticity modulus have been used as independent parameters of subsidence modeling by a support vector machine. The results indicate that the support vector machine model can model the subsidence with reasonable accuracy. To verify the performance of the support vector machine, the model's results have been evaluated with the measured values of the InSAR method obtained from the satellite images of some parts of Aliabad Plain. In addition, to examine the impact of model input parameters on subsidence, a sensitivity analysis has been conducted, and the results illustrate that the occurrence of subsidence is distinctly dependent on the drop in the underground water level in the region. The generalizability of the model has been investigated by using a new dataset, and the results indicate the generalizability of the subsidence support vector machine model.

کلیدواژه‌ها [English]

  • Land subsidence
  • Groundwater Level Dropdown
  • Machine Learning
  • Support Vector Machine
  • Aliabad plain of Qom

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  • تاریخ دریافت: 09 آبان 1401
  • تاریخ بازنگری: 29 دی 1401
  • تاریخ پذیرش: 15 بهمن 1401

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