تخمین ضریب پخش عرضی در انتقال آلودگی در رودخانه‌های عریض با استفاده از محاسبات تکاملی

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد عمران آب و سازه‌های هیدرولیکی، دانشکدۀ مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، زاهدان

2 دانشجوی دکتری مهندسی ‏عمران، دانشکدۀ مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، زاهدان

3 دانشیار گروه مهندسی عمران، دانشکدۀ مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، زاهدان

چکیده

در قرن اخیر با رشد روزافزون جمعیت شهرنشین، مشکلات متعددی در زمینۀ آلودگی و کیفیت منابع آبی مطرح شده است. بنابراین، شناخت و مطالعۀ فرایندهای اختلاط و انتقال مواد در رودخانه‌ها از جمله فعالیت‌های مهم در برنامه‌های مدیریت منابع آب به شمار می‌آید. بین فرایندهای اختلاط، پس از پدیدۀ انتشار طولی، فرایند انتشار عرضی آلودگی، تأثیرگذارترین پارامتر محسوب می‌شود. با توجه به اهمیت انتقال و چگونگی انتشار آلودگی در رودخانه‏ها، تخمین ضریب پخش عرضی انتقال آلودگی در جریان‌های سطحی با استفاده از ماشین بردار پشتیبان (SVM) و با بهره‌گیری از دو کرنل تابع پایۀ شعاعی و چندجمله‌ای و مدل درخت (MT)، هدف اصلی پژوهش حاضر است. برای تخمین ضریب پخش عرضی از 187 سری داده که شامل عمق جریان، سرعت جریان، سرعت برشی و عرض کانال می‌شود، استفاده شده است. نتایج به‌دست‌آمده از معیارهای ارزیابی نشان داد مدل SVM-Poly دقت بیشتری (992/0R= و 982/0OI=) ‌نسبت به مدل SVM-RBF دارد. همچنین مدل SVM-RBF دقت بیشتری (968/0R= و 950/0OI=) نسبت به مدل MT ‌‌(966/0R= و 946/0OI=) در تخمین این پارامتر در مرحلۀ آموزش داشت. مقادیر به‌دست‌آمده از DTدر مرحلۀ تست هم ارزیابی شدند و مشخص شد که SVM-RBF با داشتن کمترین خطا (029/0RMSE) توانایی بهتری در تخمین DT دارد. علاوه بر این، مقایسۀ عملکرد روش‌های هوشمند با روابط تجربی بیان می‌کند که روابط تجربی دقت قابل قبولی نداشته‌اند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Estimation of Transverse Dispersion Coefficient of Pollutant Transport in Rivers Using Evolutionary Computations

نویسندگان [English]

  • Asma Barahouie Nezhad 1
  • Alireza Ghaemi 2
  • Seyyed Arman Hashemi Monfared 3
  • Gholamreza Azizyan 3
  • Mohsen Dehghani Darmian 2
1 MSc. Student, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
2 Ph.D. Student, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
3 Associate Professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
چکیده [English]

Surface water is taken into account as one of the most important water resources available to mankind, which is used for various purposes, such as drinking and agriculture. Recently, with the growing urban population, there are many problems associated with the pollution and quality of water resources. Therefore, recognizing and studying the process of mixing and conveying materials in rivers is one of the prominent activities in water resource management programs. In the process of mixing, after the longitudinal dispersion coefficient, the transverse dispersion coefficient is considered as the most effective parameter. According to the importance of dispersion and distribution of pollution in rivers, in order to estimate the transverse dispersion coefficient of pollutants in surface flows, MT and SVM using two Kernels including radial basis function (RBF) and polynomial (Poly) are applied. To achieve this aim, 187 dataset including flow depth (H), flow velocity (U), shear rate (U*) and channel width (W) are used. The results of the evaluation criteria showed that the SVM-Poly model had higher accuracy (R = 0.992 = 0.92 OI =) compared to the SVM-RBF (R = 0.968 and O = 950) and MT (R = 0.966 and OI =0.946) in the training phase for DT estimation. The DT values ​​obtained by proposed models were also evaluated for testing dataset. Based on the result, it was found that SVM-RBF had the best ability to estimate DT with the lowest error (RMSE = 0.029). In addition, comparing the performance of intelligent methods with empirical relationships suggests that empirical relationships failed to show acceptable accuracy.

کلیدواژه‌ها [English]

  • Rivers
  • Pollution transport
  • Transverse dispersion coefficient
  • Support vector machine
  • Tree model
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