تحقیقات منابع آب ایران

تحقیقات منابع آب ایران

پیش‌بینی تبخیر با استفاده از تئوری آشوب و هوش مصنوعی در مناطق خشک (مطالعه موردی: استان سمنان)

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانش‌آموخته دکتری مدیریت و کنترل بیابان، دانشکده کویرشناسی، دانشگاه سمنان، سمنان، ایران.
2 دانشیار گروه بیابان‌زدایی، دانشکده کویرشناسی، دانشگاه سمنان، سمنان، ایران.
3 استاد دانشکده مهندسی عمران، دانشگاه سمنان، سمنان، ایران.
چکیده
تبخیر از پدیده‌های مهم چرخه آب‌شناختی است و پیش‌بینی آن در مدیریت، برنامه‌ریزی و حفظ آب ضروری است. از آنجائی که تئوری آشوب به مطالعه سیستم‌های دینامیکی می‌پردازد، لذا در تحقیق حاضر، پیش‌بینی فرآیند تبخیر با استفاده از ترکیب تئوری آشوب و مدل‌های هوشمند شامل ماشین بردار پشتیبان، درخت تصمیم، یادگیری گروهی، و فرآیند گوسی انجام شد و داده‌های ایستگاه سینوپتیک سمنان طی دوره زمانی 2019-1995 انتخاب شد. مقادیر بهینه میزان تأخیر و و اطلاعات متقابل با استفاده از روش‌های نزدیکترین همسایه نادرست به منظور بازسازی فضای فاز متغیر تبخیر، به ترتیب برابر با 18 و 9 بدست آمد. با توجه به ترکیب‌های متفاوتی از متغیرها، بهینه‌ترین پاسخ همه‌ی مدل‌ها برای ترکیب کلیه پارامترها مشخص شد و دو عامل تبخیر و دما بیشترین تأثیر را بر پیش‌بینی داشتند. به طور کلی، مدل ماشین بردار پشتیبان با R2 = 85.5 و  MAE = 1.4 بهترین کارایی را داشت و سپس، به‌ترتیب روش‌های فرآیند گوسی، یادگیری گروهی و روش درخت تصمیم کارایی مناسبی داشتند. استفاده ترکیبی تئوری آشوب به همراه الگوریتم‌های هوشمند از قابلیت خوبی برای تخمین تبخیر برخوردار است.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Prediction of Evaporation Using Chaos Theory and Artificial Intelligence in Dry Lands (Case Study: Semnan Province)

نویسندگان English

Fatemeh Hooshmandzadeh 1
Mohammadreza Yazdani 2
Farahad Mousavi 3
1 Ph.D. Graduate in Desert Management and Control, Faculty of Desert Studies, Semnan University, Semnan, Iran.
2 Associate Professor, Faculty of Desert Studies, Semnan University, Semnan, Iran.
3 Professor, Faculty of Civil Engineering, Semnan University, Semnan, Iran.
چکیده English

Evaporation is one of the important phenomena of the hydrological cycle and its prediction is essential for water management, planning and conservation. Since chaos theory deals with the study of dynamic systems, in this research the prediction of the evaporation process was carried out using the combination of chaos theory and intelligent models, including support vector machine, decision tree, group learning, and Gaussian process. Data of the Semnan synoptic station during the period of 1995-2019 was selected. The optimal values ​​of delay and mutual information were respectively obtained as 18 and 9 using false nearest neighbor methods in order to reconstruct the variable phase space of evaporation. According to different combinations of variables, the most optimal response of all models was determined for the combination of all parameters, and the two factors of evaporation and temperature had the greatest impact on the prediction. In general, the support vector machine model with R2 = 85.5 and MAE = 1.4 had the best performance followed by the methods of Gaussian process, group learning and decision tree method as next bests. The combined use of chaos theory along with intelligent algorithms has a good ability to estimate evaporation.

کلیدواژه‌ها English

Evaporation Forecasting
Intelligent Models
Chaos Theory
Water Conservation
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  • تاریخ دریافت 28 آبان 1402
  • تاریخ بازنگری 30 فروردین 1403
  • تاریخ پذیرش 04 اردیبهشت 1403