استفاده از روش رگرسیونی و مدل GMDH در تخمین نسبت رسوب ورودی به آبگیرهای جانبی

نویسنده
امیر مرادی نژاد
استادیار بخش آبخیزداری و حفاظت خاک مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان مرکزی.
10.22034/wmji.2024.2032135.1075
چکیده
به علت تغییراتی که در توزیع سرعت در محدوده دهانه آبگیر رخ می­دهد، معمولاً عمل رسوب­گذاری صورت می‌­گیرد که باعث کاهش راندمان آبگیری، افزایش هزینه‌­های اجرایی برای عملیات رسوب‌زدایی و درنهایت تغییر مسیر و خط‌­القعر رودخانه به سمت ساحل مقابل آبگیر می­‌شود. استفاده از سازه‌های کنترل رسوب دیوار جداکننده در جلوی آبگیر و هم‌زمان آب‌شکن در مقابل آبگیر باعث کاهش رسوب ورودی و افزایش راندمان آبگیری می‌­شود. در تحقیق حاضر تأثیر دیوار جداکننده و سازه آب‌شکن در تخمین نسبت رسوب ورودی به آبگیر به­‌صورت آزمایشگاهی، روش‌­های داده­کاوی و رگرسیون چندگانه مورد ارزیابی قرارگرفته است. ابتدا با انجام آنالیز ابعادی، نسبت‌­های بدون بعد استخراج و رابطۀ بین متغیرها و مقدار آن‌ها در آزمایش‌­ها مشخص گردید. با استفاده از نرم‌افزارهای آماری XLSTAT و SPSS از روش گام­به­گام و رگرسیون استاندارد (اینتر) معادلاتی برای ارتباط بین متغیرهای مستقل و وابسته استخراج شد. بعد از به دست آوردن معادلات خطای نسبی هر معادله محاسبه شد. سپس بهترین معادله که R2 آن بالا و خطای نسبی آن پایین بود انتخاب و پیشنهاد شد. در مرحله بعد با روش­های شبکه‌­های عصبی مصنوعی روش کنترل گروهی داده‌­ها (GMDH) مدل­سازی انجام و بهترین روش در تخمین نسبت رسوب ورودی به آبگیر انتخاب شد. نتایج نشان داد که در تخمین نسبت رسوب ورودی به آبگیر بهتـرین عملکـرد مربوط به مدل (GMDH) با شـاخص‌­هـای آمـاری 0/30,R2=0/85MAD=، 0/039RMSE= و 26/95MAPE= می‌باشد. در روش رگرسیون گام‌به‌گام 38/0,R2= 99/4 RMSE= و روش رگرسیون اینتر 0/76,R2= 4/16 RMSE= می­باشد. هم‌چنین روش‌­های داده­کاوی نسبت به روش رگرسیونی دقت بالاتری دارند.
کلیدواژه‌ها
آبگیر
آب‌شکن
دیوار جداکننده
رسوب
داده‌کاوی

عنوان مقاله English

Using the regression method and GMDH model in estimating the ratio of input sediment to lateral Intake

نویسنده English

Amir Moradinejad
Assistant Professor, Soil Conservation and Watershed Management Research Department, Markazi Agricultural and Natural Resources Research and Education Center, AREEO, Arak, Iran.
چکیده English

Due to the changes that occur in the distribution of velocity in the area of ​​the catchment opening, sedimentation usually takes place, which reduces the efficiency of water intake, increases the operational costs for sedimentation operations, and finally changes the direction and contour of the trough. The river drains towards the opposite bank. The use of sediment control structures separating the wall in front of the catchment and at the same time the breakwater in front of the catchment reduces the incoming sediment and increases the catchment efficiency. In the current research, the effect of the separating wall and the breakwater structure in estimating the ratio of incoming sediment to the catchment has been evaluated by laboratory and data mining and multiple regression methods. First, by performing dimensional analysis, dimensionless ratios were extracted and the relationship between the variables and their value in the experiments was determined. Using XLSTAT and SPSS statistical software, equations for the relationship between independent and dependent variables were extracted from the step-by-step and inter method. After obtaining the equations, the relative error of each equation was calculated. Then the best equation with high R2 and low relative error was selected and proposed. In the next step, modeling was done with the methods of artificial neural networks and the method of group data control (GMDH) and the best method was selected to estimate the ratio of input sediment to the catchment. The results showed that in estimating the ratio of input sediment to the catchment, the best performance is related to the model (GMDH) with statistical indices, R2=0.850, MAD=0.03, RMSE=0.039 and MAPE=26.95. In the step-by-step regression method, R2=0.38, RMSE=4.99 and inter regression method, R2=0.76, RMSE=4.16. also data-mining methods compared to the method Regression has higher accuracy.

کلیدواژه‌ها English

aquifer
breakwater
separating wall
sediment
data-mining
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