نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجو
2 دانشیار گروه مهندسی آب
3 استادیار گروه مهندسی آب
4 استادیار گروه مهندسی آب، دانشگاه لرستان
چکیده
پیش‌بینی جریان رودخانه‌ها یکی از مهم‌ترین موارد کلیدی در مدیریت و برنامه‌ریزی منابع آب به‌ویژه اتخاذ تصمیمات صحیح در مواقع سیلاب و بروز خشک‌سالی‌ها است. برای پیش‌بینی میزان جریان رودخانه‌ها رویکردهای متنوعی در هیدرولوژی معرفی‌شده است که مدل‌های هوشمند از مهم‌ترین آن‌ها می‌باشند. در این پژوهش کاربرد مدل هیبریدی ماشین بردار پشتیبان_ موجک به منظور برآورد دبی رودخانه های حوضه آبریز دز براساس آمار آبدهی روزانه ایستگاه‌های هیدرومتری واقع در بالادست سد طی دوره آماری(1397-1387) مورد بررسی و ارزیابی قرار گرفته و کارایی آن با مدل ماشین بردار پشتیبان مقایسه شد. معیارهای ضریب تبیین، ریشه میانگین مربعات خطا، میانگین قدر مطلق خطا و ضریب نش ساتکلیف برای ارزیابی و مقایسه مدل‌ها مورد استفاده قرار گرفت. نتایج نشان داد ساختارهای ترکیبی نتایج قابل قبولی در مدل‌سازی دبی رودخانه ارائه می نمایند. همچنین مقایسه مدل‌ها طبق معیارهای ارزیابی نشان داد مدل هیبریدی ماشین بردار پشتیبان-موجک عملکرد بهتری در پیش‌بینی جریان داشته و میتواند در زمینه پیش بینی دبی روزانه جریان مفید باشد.
کلیدواژه‌ها
عنوان مقاله [English]
Application of Wavelet Support Vector machine (WSVM) model in Predicting River Flow (Case study: Dez basin)
نویسندگان [English]
- Reza Dehghani 1
- hassan torabi 2
- hojatolah younesi 3
- babak shahinejad 4
1 Student
2 Associate Professor, Department of Water Engineering
3 Assistant Professor of Water Engineering Department
4 Assistant Professor Department of Water Engineering
چکیده [English]
River flow prediction is one of the key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and droughts. To predict the flow rate of rivers, various approaches have been introduced in hydrology, the most important of which are the intelligent models. In this study, a hybrid, model wavelet- support vector machine, was applied to estimate the discharge of Dez river basin based on the daily discharge statistics provided by the hydrometric stations located at the upstream of the dam during the statistical period (2008-2018) and its performance was compared with the support vector machine model. The correlation coefficients, root mean square error, and mean absolute error was used for evaluation and a comparison of the performance of models. The results showed that the hybrid structures presented acceptable outcomes in the modeling of river discharge. A comparison of models also showed that the hybrid model of wavelet -support vector machine has a better performance in forecasting the flow. In conclusion, the use of the WSVM model could be effective in estimating flood peak discharge.
کلیدواژه‌ها [English]
- Forecasting
- Dez Basin
- Support Vector Machine
- Wavelet
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