مدل‌سازی عملکرد محصولات دیمی گندم، جو و یونجه با استفاده از رگرسیون بردار پشتیبان و برنامه‌ریزی ژنتیک

نویسندگان

1 دانش آموخته کارشناسی ارشد مهندسی آب، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز

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

3 استاد، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز

چکیده

تغییر اقلیم، افزایش دمای جهانی، بحران آب و رشد جمعیت جهان موجب شده است که تأمین غذای مردم دنیا تبدیل به یک چالش در بین پژوهشگران شود. برهمین ‌اساس پیش‌بینی و شبیه‌سازی تولیدات گیاهی متناسب با شرایط آب‌ و ‌هوایی، امری ضروری است. در تحقیق حاضر، ارتباط عوامل اقلیمی و شاخص‌های خشکسالی با میزان تولید گیاهان گندم، جو و یونجه که به‌صورت دیم زیر کشت قرار گرفته‌اند، در سه منطقه در استان آذربایجان‌شرقی مورد مطالعه قرار گرفت. بدین منظور، برای هر یک از متغیرهای دما، بارندگی، تبخیر- تعرق ‌و شاخص‌های خشکسالی SPI و RDI، بازه‌های زمانی سه تا نه ماهه در دوره زمانی 1383تا 1393 در نظر گرفته شد و با استفاده از روش‌های داده محور رگرسیون بردار پشتیبان (SVR) و برنامه‌ریزی ژنتیک (GP)، مقدار تولید سه گیاه مذکور پیش‌بینی گردید. علاوه بر این، دقت روش‌های مذکور در پیش‌بینی عملکرد محصولات کشت دیم، با استفاده از پارامترهای آماری جذر میانگین مربعات خطا (RMSE) و میانگین خطای مطلق (MAE) مورد بررسی قرار گرفت. نتایج نشان داد در شهر تبریز برای محصول یونجه روش GP با (kg ha-1) 17/0RMSE=، در شهر مراغه برای محصول یونجه روش SVR با (kg ha-1)56/0RMSE= و در شهر سراب برای محصول جو روش SVRبا (kg ha-1) 20/0RMSE= پیش‌بینی‌های دقیق‌تری ارائه کرده‌اند. می‌توان بیان داشت استفاده از عوامل آب ‌و‌ هوایی و شاخص‌های خشکسالی در دوره‌ها‌ی زمانی پاییز- زمستان- بهار تاثیر بسزایی بر افزایش دقت روش‌های داده محور در پیش‌بینی عملکرد محصولات دیم دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling the yield of rainfed wheat, barley and alfalfa products using support vector regression and genetic programming

نویسندگان [English]

  • Solmaz Panahi 1
  • Saeed Samadianfard 2
  • Amir Hossein Nazemi 3
1 MSc Graduate of Irrigation and Drainage Engin., Dept. of Water Engin., Faculty of Agric., Univ. of Tabriz, Tabriz, Iran
2 Assist. Prof., Dept. of Water Eng., Faculty of Agric., University of Tabriz, Iran
3 Professor, Dept. of Water Engin., Faculty of Agric., Univ. of Tabriz, Tabriz, Iran
چکیده [English]

Climate change, the rise of global temperature, the water crisis, along with the growth of the world's population have made the world's food supply a challenge for researchers. For this reason, it is necessary to predict and simulate plant products in accordance with the climatic conditions. In this study, the relationships of meteorological parameters and standard precipitation index (SPI) and reconnaissance drought index (RDI) with yields of the rainfed wheat, barley and alfalfa plants were studied in three regions in East Azarbaijan province. For each of the temperature, rainfall, evapotranspiration and SPI and RDI parameters, the time intervals of three to nine months were considered in the period from 2004 to 2014. Then, using support vector regression (SVR) and genetic and programming (GP), the production amounts of the three studied plants were predicted. In addition, the accuracy of the mentoned methods in predicting the performance of dry crop products was evaluated using root mean squared error (RMSE) and mean absolute error (MAE) statistics. Results showed that in Tabriz for alfalfa, GP method with RMSE= 0.17 (kg ha-1), in Maragheh for the alfalfa, SVR with RMSE= 0.56 (kg ha-1) and in Sarab for barely, SVR method with RMSE=0.20 (kg ha-1) had more precise predictions. It can be stated that the use of climatic factors and drought indicators of autumn, winter and spring seasons have significant effects on increasing the accuracy of soft computing techniques in predicting the performance of rainfed products.

کلیدواژه‌ها [English]

  • Meteorological parameters
  • Modeling
  • Production reduction
  • Rainfed products
  • Soft computing

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دانش آب و خاک
دوره 32، شماره 2
تیر 1401
صفحه 97-111

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