معرفی یک روش ترکیبی برای تخمین سرعت باد با استفاده از اطلاعات ایستگاه‌های همسایه در استان اصفهان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران کرج، ایران

2 استادیار گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران، کرج، ایران

چکیده

 پیش­بینی مؤلفه­های باد ازجمله سرعت باد یکی از عوامل مهم به­خصوص در بحث تبخیر در یک حوزه آبخیز محسوب می­شود. در این مقاله برای افزایش کارایی مدل­ ماشین بردار پشتیبان در پیش‌بینی سرعت باد، این مدل با الگوریتم بهینه‌سازی کرم شب‌تاب  ترکیب‌شد که منبعد به عنوان مدل ترکیبی از آن یاد می­شود. در این راستا با استفاده از داده­های سرعت باد ایستگاه­های همدید استان اصفهان، مقادیر سرعت باد ماهانه در ایستگاه­های مجهول همسایه در مقیاس ماهانه برآورد شد و سپس کارایی مدل­های ماشین بردار پشتیبان و مدل ترکیبی مورد مقایسه قرار گرفت. در نهایتبا استفاده از معیارهای RMSE، MAE، WI و NS،  کارآیی عملکرد دو مدل مورد ارزیابی قرار گرفت.  نتایج نشان داد که در مرحله ارزیابی، مدل ترکیبی با مقادیر همبستگی بالا و خطای کم­تر کارآیی بالاتری نسبت به مدل دیگر دارد. همچنین روش استفاده از داده­های ایستگاه­های همسایه به‌عنوان ورودی مدل­های تخمین­گر  ایستگاه مجهول، روش مناسبی برای تخمین سرعت باد می­باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Introducing a Hybrid Method for Estimating Wind Speed Using Information from Neighboring Stations in Isfahan Province

نویسندگان [English]

  • Babak Mohammadi 1
  • Zahra Aghashariatmadari 2
1 Irrigation & Reclamation Engrg. Dept. University of Tehran Karaj, Iran.
2 Zahra Shariatmadari Assistant Prof., Irrigation & Reclamation Engrg. Dept. University of Tehran Karaj, Iran.
چکیده [English]

The prediction of wind components including wind speed is one of the important factors, especially in the case of evaporation in a watershed. In this paper, in order to increase the efficiency of support vector machines (SVM) for predicting wind speed, the SVM model was combined with the firefly optimization algorithm called hybrid model (HM). In this regard, the wind speed data from synoptic stations of Isfahan province were used to estimate the monthly wind speed values of the unknown neighboring stations. Then, the efficiency of the SVM and HM models was compared. Finally, the RMSE, MAE, WI, and NS indices were used to evaluate the both models performance efficiency.  The results in the evaluation step showed that the hybrid model (HM) with high correlation and lower error values has higher performance efficiency as compared to the SVM model. as Also, the method of using neighboring stations data as inputs for the predictive models of unknown station is a proper method for estimation of wind speed.

کلیدواژه‌ها [English]

  • Isfahan
  • firefly optimization algorithm
  • neighboring station
  • hybrid method
  • wind speed
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