بررسی کارآیی روش‌های هوش مصنوعی در پیش‌بینی عملکرد تصفیه‌‌خانه فاضلاب (مطالعه موردی: تصفیه‌خانه فاضلاب شهر تبریز)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی منابع آب، دانشکده مهندسی عمران، دانشگاه تبریز

2 گروه مهندسی عمران-آب، دانشکده مهندسی عمران، دانشگاه تبریز، تبریز، ایران

3 گروه مهندسی عمران، دانشگاه آزاد اسلامی واحد اهر، ایران

چکیده

افزایش نگرانی در مورد مسائل زیست‌محیطی متخصصین را تشویق کرده است که توجه خود را روی عملکرد و کنترل درست تصفیه‌خانه‌های فاضلاب (WWTPS) متمرکز کنند. در مطالعه حاضر دو روش شبکه عصبی مصنوعی و ماشین بردار پشتیبان برای مدل‌سازی کیفیت پساب خروجی تصفیه‌خانه فاضلاب شهر تبریز مورد استفاده قرار گرفته است. داده‌های ورودی شامل پارامتر‌های BODinf، CODinf، TSSinf و PHinf فاضلاب در ورودی تصفیه‌خانه تبریز است که برای پیش‌بینی مقادیر متناظر مشخصه‌های BODeff، CODeff و TSSeff در پساب خروجی تصفیه‌خانه به کار برده شده است. داده‌ها بصورت میانگین روزانه، هفتگی و ماهانه مورد بررسی قرار گرفته است. بر طبق نتایج، هر دو روش ذکر شده، دارای عملکرد بهتری در مدل‌سازی پارامترهای کیفیت پساب خروجی تصفیه‌خانه تبریز به صورت ماهانه می‌باشد. مقادیر عددی معیارهای ارزیابی، R2، RMSE و DC مربوط به داده‌های تست ماهانه برای مدل برتر روش شبکه عصبی به ترتیب برای BODeff 87/0، 86/2 و 76/0، برای CODeff 859/0، 51/4 و 715/0، و برای TSSeff 8/0، 2 و 63/0 بدست آمد و مقادیر عددی معیارهای ارزیابی، R2، RMSE و DC مربوط به داده‌های تست ماهانه برای مدل برتر روش ماشین بردار پشتیبان به ترتیب برای BODeff 88/0، 8/2 و 77/0، برای CODeff 86/0، 38/4 و 73/0، و برای TSSeff 79/0، 03/2 و 62/0 بدست آمد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigation of Artificial Intelligence Approaches Capability in Predicting the Wastewater Treatment Plant Performance (Case Study: Tabriz Wastewater Treatment Plant)

نویسندگان [English]

  • Mohammad Taghi Aalami 1
  • Nasim Hejabi 2
  • Vahid Nourani 1
  • SEYEDMAHDI SAGHEBIAN 3
1 Department of Water Engineering , Faculty of civil Engineering, University of Tabriz
2 Department of Water Engineering, Faculty of Civil, University of Tabriz, Tabriz, Iran
3 Department of Civil Engineering, Ahar Branch, Islamic Azad University – Ahar - Iran
چکیده [English]

Due to the excessive concern about environmental issues, researchers had to come up with a better solution to control the Wastewater treatment plants (WWTPs).In this research, two approaches, including Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used for modeling the effluent quality of the Tabriz Wastewater Treatment Plant. Input data of models consist ofBODinf, CODinf, TSSinf, and PHinf of influent sewage related to Tabriz Treatment Plant which has been used to predict the corresponding value of BODeff, CODeff, and TSSeff concerning the treatment plant effluent. The daily, weekly, and monthly average data have been studied. According to the results, the two approaches mentioned, have the best performance in the prediction of the monthly average dataset of effluent parameters of Tabriz Wastewater Treatment Plant.
 

کلیدواژه‌ها [English]

  • Wastewater treatment plant
  • Artificial Intelligence Models
  • artificial neural network
  • Support Vector Machine
  • Effluent quality of Wastewater Treatment Plant
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