بررسی دقت مدل‏ های ANFIS، SVM و GP در مدل‏ سازی مقادیر دبی جریان رودخانه

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی دکتری منابع آب، دانشکدۀ کشاورزی، دانشگاه بیرجند

2 استادیار دانشکدۀ کشاورزی، دانشگاه بیرجند

3 دانشجوی دکتری منابع آب، دانشکدۀ علوم آب، دانشگاه شهید چمران اهواز

4 دانشجوی دکتری آبخیزداری، دانشکدۀ کشاورزی و منابع طبیعی، دانشگاه کاشان

چکیده

پیش‏بینی دقیق جریان رودخانه‏ها در مدیریت بهینۀ منابع آب‏های سطحی اهمیت به‏سزایی دارد. یافتن مدل مناسب برای پیش‏بینی دقیق این پارامتر یکی از راه‏های مهم اقدامات در شبیه‏سازی و پیش‏بینی است. در این مطالعه سه مدل ANFIS، SVM و GP برای مدل‏سازی دبی ماهانۀ رودخانۀ نازلوچای در محل ایستگاه هیدرومتری تپیک واقع در غرب دریاچۀ ارومیه تحت تأثیر بارش حوضۀ رودخانۀ مطالعه‌شده بررسی و مقایسه شد. در همۀ روش‏های یادشده الگوهای M1 تا M5 داده‏های دبی جریان با تأخیر یک تا پنج و الگوهای M6 تا M10 الگوی ترکیبی با داده‏های بارش و دبی و با تأخیرهای یک تا پنج ماه بررسی شدند. برای بررسی مقادیر خطای ناشی از مدل‏سازی از سه روش ضریب تبیین، مجذور میانگین مربعات خطا و معیار کارایی مدل استفاده شد. نتایج بررسی دقت و میزان خطای مدل‏ها نشان داد الگوی ترکیبی فقط در مدل SVM بهترین نتیجه را داده است و در دو مدل GP و ANFIS الگوهای تک‌سری بهترین نتیجه را ارائه کردند. از بین سه مدل بررسی‌شده، مدل ANFIS با الگوی ورودی چهار و پنج تأخیر بهترین نتیجه را داد. به‌طور کلی، نتایج نشان داد با به‌کارگیری مدل ANFIS در مدل‏سازی دبی جریان ماهانۀ رودخانۀ نازلوچای، خطای مدل نسبت به دو مدل GP و SVM به‌ترتیب حدود 23 و 3 درصد (در واحد دبی جریان) کاهش و دقت مدل نیز نسبت به دو مدل GP و SVM به‌ترتیب حدود 10 و 4 درصد افزایش می‏یابد.
 


 

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Evaluation the Accuracy of ANFIS, SVM and GP Models to Modeling the River Flow Discharge

نویسندگان [English]

  • Mohammad Nazeri Tahroudi 1
  • Seyed Reza Hashemi 2
  • Farshad Ahmadi 3
  • Zahra Nazeri Tahroudi 4
1 Ph.D Student of Water Resources Management, Birjand University, Birjand, Iran.
2 Department of Water Engineering, Birjand University, Birjand
3 Ph.D Student of Water Resources Management, Shahid Chamran University, Ahwaz, Iran.
4 Ph.D Student of Watershed, Kashan University, Kashan, Iran.
چکیده [English]

Prediction the river flow discharge values are important in the surface water resources management. Find an appropriate model to accurately predictionof this parameter is one of the most important ways to simulation and prediction. In this study three ANFIS, SVM and GP models were evaluated and compared to modeling the monthly flow discharge of Nazloochi River in Tapik hydrometric station that located in western of Urmia Lake based on precipitation of river basin. All the methods listed in M1 to M5 data flow patterns with a delay of 1 to 5 M6 to M10 and patterns of precipitation and discharge data combined with delays of one to five months were studied.To investigate the value of modeling’s error three coefficient of determination, root mean square error and effectiveness criteria tests were used. The results of evaluation the accuracy and error values of models indicated that the combined pattern has better results only in SVM model and in GP and ANFIS models the ones series patterns presented the better results. Among the three studied models, ANFIS model with 4 and 5 delays input patterns presented the best results. Overall the results indicated that with adoption of ANFIS model to modeling the monthly river flow in Nazloochai River, error values were decreased about 23 and 3 percentages respectively in GP and SVM models and accuracy of modeling compared to GP and SVM models were increased about 10 and 4 percent respectively.
 
 
 

کلیدواژه‌ها [English]

  • Flow discharge
  • Genetic Algorithm
  • Support vector machine
  • Urmia Lake
 
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