دوره 8، شماره 16 - ( پاییز و زمستان 1396 )
جلد 8 شماره 16 صفحات 187-178 |
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(2018). Estimation of Rivers’ Electrical Conductivity using Wavelet Neural Network
(Case study: Kakareza River)
. jwmr. 8(16), 178-187. doi:10.29252/jwmr.8.16.178
URL: http://jwmr.sanru.ac.ir/article-1-914-fa.html
URL: http://jwmr.sanru.ac.ir/article-1-914-fa.html
قربانی محمدعلی، دهقانی رضا. تخمین هدایت الکتریکی رودخانه ها با استفاده از شبکه عصبی موجک
(مطالعه موردی: رودخانه کاکارضا)
پژوهشنامه مديريت حوزه آبخيز 1396; 8 (16) :187-178 10.29252/jwmr.8.16.178
چکیده: (3197 مشاهده)
هدایت الکتریکی (EC) عامل مهمی در مهندسی رودخانه و بویژه مطالعه کیفی آب رودخانه‌ها می‌باشد. در این پژوهش کاربرد شبکه عصبی موجک، جهت پیش‌بینی هدایت الکتریکی رودخانه کاکارضا موردبررسی و ارزیابی قرار گرفت و نتایج آن با مدل شبکه عصبی مصنوعی مقایسه شد. که برای این منظور هیدروژن کربنات، کلرید، سولفات، کلسیم، منیزیم، سدیم و دبی جریان در مقیاس زمانی ماهانه در طی دوره آماری (1393-1347) بعنوان ورودی و هدایت الکتریکی بعنوان پارامتر خروجی انتخاب گردید. معیارهای ضریب همبستگی، ریشه میانگین مربعات خطا و ضریب نش ساتکلیف برای ارزیابی و عملکرد مدل مورد استفاده قرار گرفت. نتایج حاصله نشان داد مدل شبکه عصبی موجک دارای بیشترین ضریب همبستگی (977/0)، کمترین ریشه میانگین مربعات خطا( ds/m032/0) و نیز بیشترین معیار نش ساتکلیف (847/0) در مرحله صحت سنجی در اولویت قرار گرفت. درمجموع نتایج نشان داد مدل شبکه عصبی موجک در تخمین مقادیر حداقل و حداکثر دقت بالایی از خود نشان داده است. نتایج حاکی از توانمندی قابل‌قبول مدل شبکه عصبی موجک در تخمین هدایت الکتریکی آب رودخانه‌ها است.
نوع مطالعه: پژوهشي |
موضوع مقاله:
تخصصي
دریافت: 1396/11/10 | ویرایش نهایی: 1396/12/5 | پذیرش: 1396/11/10 | انتشار: 1396/11/10
دریافت: 1396/11/10 | ویرایش نهایی: 1396/12/5 | پذیرش: 1396/11/10 | انتشار: 1396/11/10
فهرست منابع
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