کاربرد رگرسیون چندمتغیره و برنامه ریزی بیان ژن در مدل سازی تبخیرتعرق مرجع (مطالعه موردی: ایستگاه خرم آباد)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی آبیاری و زهکشی، دانشکده کشاورزی، دانشگاه لرستان.

2 استادیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه لرستان

3 استادیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه لرستان.

چکیده

در این پژوهش به­منظور تخمین تبخیرتعرق مرجع در ایستگاه خرم­آباد، روش­های رگرسیون چندمتغیره و برنامه­ریزی بیان ژن مورد بررسی و استفاده قرار گرفتند. برای اطلاعات ورودی مدل از اطلاعات ایستگاه سینوپتیک خرم­آباد شامل: درجه حرارت حداکثر و حداقل، ‏رطوبت نسبی حداکثر و حداقل، ساعات آفتابی و سرعت باد ماهانه در بازه زمانی 1395-1361 (به تعداد 420 ماه) استفاده شد. بر اساس رابطه بین پارامترهای ورودی و خروجی، شش الگوی ورودی برای مدل­سازی تعیین گردید. 70 درصد داده­ها برای آموزش و 30 درصد داده­ها برای صحت­سنجی مدل­ها به­کار گرفته شد، هم­چنین در روش برنامه­ریزی بیان ژن دو نوع عملگر ریاضی شامل چهار عملگر اصلی و عملگرهای پیش­فرض مدل مورد بررسی قرار گرفتند. نتایج حاصل از رگرسیون چندمتغیره نشان ­داد که مدل پیشنهادی با مقدار 952/0 =R2 از دقت قابل­قبولی برخورداراست. تحلیل ضرایب مدل حاکی از بیشترین تأثیر حداکثر درجه حرارت با ضریب 604/0 بر تبخیرتعرق مرجع بود. نتایج برنامه­ریزی بیان ژن نشان داد الگوی پنجم با عملگرهای چهار اصلی، در مرحله آموزش با ‏958/0 ‏R2=، ‏‎‏704/0‏RMSE= و 97/0NS= و مرحله آزمون با 977/0 R2=،  ‏‏‎‎‏615/0‏RMSE= و 977/0NS= عملکرد بهتری را داشته و نتایج به‌دست‌آمده نشان داد که برنامه­ریزی بیان ژن دارای توانایی قابل قبولی در تخمین تبخیرتعرق مرجع تحت شرایط آب‌وهوایی خرم­آباد بوده و به‌عنوان مدل قابل­استفاده در این زمینه معرفی کرد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Application of Multivariate Regression and Gene Expression Programming in Modeling Reference Evapotranspiration (Case Study: Khorramabad Station)

نویسندگان [English]

  • Yaser Sabzevari 1
  • Aliheidar Nasrollahi 2
  • Majid Sharifipour 3
  • babak shahinejad 3
1 MSc student, Department of Water Engineering, Faculty of Agriculture and Natural Resources, Lorestan ‎University.‎
2 Assistant Professor, Department of Water Engineering, Faculty of Agriculture and Natural Resources, ‎‎Lorestan University.(
3 Assistant Professor, Department of Water Engineering, Faculty of Agriculture and Natural Resources, ‎‎Lorestan University.‎‏
چکیده [English]

Accurate estimation of water requirements of plants is a key factor in controlling several hydrological processes including: planning and management of water resources, especially in arid and semi-arid regions (Laaboudi et al., 2012; Wen et al., 2015) water pricing and water requirement for Irrigation (Yassin et al., 2016). In this study, multivariate regression methods and gene expression planning were evaluated to estimate reference evapotranspiration. For model input data, the Khorramabad Synoptic Station information including: maximum and minimum temperatures, maximum and minimum relative humidity, sunny hours and monthly wind speeds in the range of 1983-2017(420 months) were used. Based on the relationship between input and output parameters, six input patterns were determined for modeling.70% of the data were used for training and 30% were used for model validation.The results of multivariate regression showed that the proposed model had acceptable accuracy with R2 = 0.952.The analysis of model coefficients showed the greatest effect of maximum temperature with a coefficient of 0.604 on reference evapotranspiration. Gene expression planning results showed that the fifth pattern with four main operators was R2 = 0.958 and RMSE = 0.704 in the training phase and R2=0.977 and RMSE = 0.615 in the test phase had better performance.

کلیدواژه‌ها [English]

  • Correlation
  • FAO Penman Monteith
  • GEP
  • Regression

مراجع

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علوم و مهندسی آبیاری
دوره 45، شماره 1
اردیبهشت 1401
صفحه 35-48

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سابقه مقاله

  • تاریخ دریافت: 20 آبان 1398
  • تاریخ بازنگری: 10 مرداد 1399
  • تاریخ پذیرش: 12 مرداد 1399
  • تاریخ انتشار: 01 اردیبهشت 1401

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