کاربرد روش الگوریتم ژنتیک در برآورد پارامترهای سری زمانی خطی به منظور پیش‌بینی خشکسالی

نویسندگان

1 دانش‌آموخته دکتری مهندسی منابع آب، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه

2 استادیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه

3 دانشیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه

4 استادیار گروه مهندسی عمران، دانشکده مهندسی عمران، دانشگاه صنعتی ارومیه، ارومیه

چکیده

به­طور متداول برآورد پارامترهای سری زمانی خطی بر اساس روش­های گرافیکی و تقریبی است. بنابراین استفاده از رویکردی جدید جهت افزایش سرعت و سهولت در دسترسی به بهترین مدل سری زمانی می­تواند نقش مهمی در استفاده از این روش در پیش­بینی وقایع هیدرولوژیک داشته باشد. در این تحقیق جهت تخمین پارامترهای سری زمانی آرما از رویکرد بهینه­سازی بر مبنای الگوریتم ژنتیک استفاده شده است. در این مطالعه با استفاده از روش ترکیبی الگوریتم ژنتیک – آرما پیش­بینی خشکسالی در سه ایستگاه منتخب حوضه آبریز دریاچه ارومیه شامل تبریز، سقز و ارومیه بر اساس شاخص خشکسالی SPEI مورد بررسی قرار گرفت. نتایج نشان داد که بر اساس آزمون BDS در هر سه ایستگاه و در همه مقیاس­های زمانی سری قابلیت پیش­بینی پذیری را دارد. همچنین به منظور بررسی میزان قابلیت اطمینان به مدل پیش­بینی، از آماره Ljung-Box استفاده شد که مقادیر p-value آن در همه ایستگاه­ها و مقیاس­های زمانی بزرگتر از 05/0 می­باشد که نشانگر تصادفی بودن باقی­مانده­های مدل و قابل اطمینان بودن آن است. همچنین بهترین مدل سری زمانی در مقیاس­های زمانی مختلف محاسبه و بر اساس آن پیش­بینی شاخص SPEI انجام گرفت. نتایج بخش پیش­بینی نشان داد که روش ترکیبی الگوریتم ژنتیک – آرما در مقیاس­های زمانی بلندمدت شاخص SPEI در همه ایستگاه­ها از دقت مناسب برخوردار است، ولی در مقیاس­های زمانی کوتاه­مدت عملکرد آن مناسب نمی­باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Application of Genetic Algorithm in Estimation of Linear Time Series Parameters for the Purpose of Drought Prediction

نویسندگان [English]

  • Abbas Abbasi 1
  • keivan khalili 2
  • Javad Behmanesh 3
  • Akbar Shirzad 4
1 Ph.D. Graduate, Dept. of Water Eng., Faculty of Agric., Univ. of Urmia, Urmia, Iran
2 Assist. Prof., Dept. of Water Eng., Faculty of Agric., Univ. of Urmia, Urmia, Iran
3 Prof., Dept. of Water Eng., Faculty of Agric., Univ. of Urmia, Urmia, Iran
4 Assist. Prof., Faculty of Civil Engineering, Urmia University of Technology, Urmia, Iran
چکیده [English]

So far, the linear time series parameters are estimated, generally based on graphical and approximate methods. Therefore, the use of a new approach to increase the speed and ease of access to the best time series model can play an important role in using this method for predicting hydrological events. In this research, an optimization approach based on genetic algorithm has been used to estimate the ARMA time series parameters. A hybrid of Genetic Algorithm-ARMA method was used to drought prediction at three selected stations in the Urmia Lake basin, including Tabriz, Saqhez and Urmia, based on the SPEI drought index. The results showed that according to the BDS test, the model had the ability to predict the drought in all three stations and in all time scales. The Ljung-Box statistic was also used to evaluate the reliability of the prediction model. Its p-value at all stations and time-scales were greater than 0.05 which indicated the residuals of models were random and reliable. Also, the best time series model was calculated at different time scales and based on this, the SPEI index was predicted. The results of the prediction section showed that ARMA-GA hybrid method had a high accuracy at all long-term time scales of SPEI index at all the stations, but its performance was not suitable for short-term time scales.

کلیدواژه‌ها [English]

  • Drought
  • Estimated parameters
  • Genetic Algorithm
  • Time series
  • Urmia Lake
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