تحقیقات منابع آب ایران

تحقیقات منابع آب ایران

بررسی قابلیت روش ماشین بردار پشتیبان و تبدیل موجک در پیش‌بینی کمیت و کیفیت آب (مطالعه موردی: تالاب انزلی)

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشجوی دکتری، گروه مهندسی آب، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران.
2 استاد گروه مهندسی آب، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران.
3 استادیار گروه کشاورزی، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران.
چکیده
در این پژوهش به منظور تهیه یک زیرساخت پیش‌بینی عددی از وضعیت تغییرات کمیت و کیفیت تالاب انزلی، از قابلیت روش ماشین بردار پشتیبان و تبدیل موجک استفاده شده است. با توجه به لزوم سنجش دقیق پیش‌بینی‌های اقلیمی از آمار موجود کمی و کیفی جریانات سطحی، از داده‌های صحرایی و رقوم زمینی در یک بازه زمانی 20 ساله از سال 1380 تا 1399 به صورت پایه محاسبات با پیش‌‎پردازش در محیط نرم‌‎افزاری پایتون استفاده شد. نتایج در این مورد حاکی از تطابق بالای رگرسیون استخراج شده با تابع RBF در مقابل رگرسیون خطی محیط اکسل در روش تجربی بود. همچنین، پس از تأیید روش تجربی با استفاده از مدل SVM، اقدام به توسعه یک مدل تبدیل موجک به جهت تعیین نهایی پارامتر تبدیل موجک مداوم شد. نتایج نشان داد که مقدار تابع هدف در بازه داده 2- تا 2 در تابع شعاعی و مدل خطی تقریباً مقدار نزدیک به هم در بازه 0/9- تا 0/1 بوده است؛ اما این اعداد در تابع چند جمله‌‎ای متفاوت بوده است که نتایج حاکی از تطابق بالای رگرسیون استخراج شده با تابع RBF در مقابل رگرسیون خطی محیط اکسل در روش تجربی بود. همچنین، نتایج نشان داد که مدل پیش‌بینی SVM به خوبی برازش تابع RBF را بر داده‌‎ها مطابق با برازش رگرسیون خطی در روش تجربی کشف روند و سری زمانی داده‎‌های کاربر استخراج کرد. نتایج در این مورد حاکی از CWT با تراکم چهار در دوره‌­های ثبتی است.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Investigating the Ability of Support Vector Machine and Wavelet Transform Method in Predicting Water Quantity and Quality (Case Study: Anzali Lagoon)

نویسندگان English

Seyed Saman Mirfallah Nasiri 1
Ebrahim Amiri 2
Jalal Behzadi 3
1 Ph.D. Student, Department of Water Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran.
2 Professor, Department of Water Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran.
3 Assistant Professor, Department of Agriculture, Lahijan Branch, Islamic Azad University, Lahijan, Iran.
چکیده English

In this research, a numerical prediction infrastructure is developed using the support vector machines and the wavelet transform to predict the changes of water quantity and quality in Anzali lagoon. Due to the necessity of accurate measurement of climate forecasts from the existing quantitative and qualitative statistics of the surface flow, field data and ground level in a 20-year period from 1999 to 2020 were pre-processed in PYTHON software environment and used as the calculation base. The results indicated that the regression extracted with the RBF function had a high match compared to the linear regression. Also, after confirming the experimental method using the SVM model, a wavelet transform model was developed to determine the final parameter of CWT. The results showed very close values for the target function in the radial function and the linear model in the data range of -2 to 2 in the range of -0. 9 to 0. 1. But these numbers were different in the polynomial function, which indicated a high compatibility of the regression extracted with the RBF function compared to the linear regression. Also, the results showed that the SVM prediction model well fitted the RBF function on the data in accordance with the linear regression fitting in the experimental method of discovering the trend and the time series of the user's data. The results in this case indicated CWT with a density of four in the recorded periods in accordance with the images.

کلیدواژه‌ها English

Flow Model
Anzali Lagoon
SVM
Wavelet
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  • تاریخ دریافت 29 آذر 1402
  • تاریخ بازنگری 14 اسفند 1402
  • تاریخ پذیرش 20 اسفند 1402