پیش بینی تقاضای آب در بخش کشاورزی استان های حاشیه دریای خزر: مقایسه الگوی مارکوف-سوئیچینگ و شبکه عصبی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری اقتصاد کشاورزی، دانشگاه آزاد اسلامی، واحد قائم‏شهر، قائم‏شهر، ایران.

2 نویسنده مسئول و استادیار گروه اقتصاد کشاورزی، دانشگاه آزاد اسلامی، واحد قائم‏شهر، قائم‏شهر، ایران.

3 استادیار گروه اقتصاد کشاورزی، دانشگاه آزاد اسلامی، واحد قائم‏شهر، قائم‏شهر، ایران.

چکیده

در جهان امروز، مدیریت عرضه و تقاضای آب نقش محوری در سامان‏دهی و برنامه ­ریزی تأمین آب شرب ساکنان شهر­ها و روستا­ها و همچنین،تأمین منابع آب کشاورزان و صنعت­ گران دارد، به ‏ویژه آنکه در وضعیت کنونی، تمام کشورهای جهان با تبعات تغییرات اقلیمی نیز مواجه ‏اند. در این راستا، در پژوهش حاضر، به پیش­بینی تقاضای آب بخش کشاورزی استان ­های حاشیه دریای خزر به روش زنجیره مارکوف- سوئیچینگ و مقایسه آن با مدل شبکه عصبی مصنوعی با بهره‌گیری از داده‌های فصلی دوره 1380:1 تا 1397:4 پرداخته شد. مقایسه کارآیی مدل­ های تقاضای آب برآوردشده به روش شبکه عصبی مصنوعی و چرخشی مارکوف با استفاده از معیارهای میانگین مربع خطا (MSE)، مجذور میانگین مربع خطا (RMSE)، میانگین قدرمطلق خطا (MAE)، و میانگین قدرمطلق درصد خطا (MAPE) نشان داد که رویکرد چرخشی مارکوف، نسبت به مدل ­های شبکه عصبی، برای پیش­بینی تقاضای آّب،کارآیی بیشتری دارد. همچنین، پیش‌بینی تقاضای آب کشاورزی برای دو دوره فصلی و سالانه، به ‏ترتیب،طی دوره‏های 1398:1 تا 1402:4 و 1398 تا 1402 صورت گرفت.

کلیدواژه‌ها


عنوان مقاله [English]

Prediction of Water Demand in the Agricultural Sector of the Caspian Littoral Provinces: Comparison of Markov-Switching and ANN Models

نویسندگان [English]

  • M. Khoshmo 1
  • M. Goodarzi 2
  • G. Norouzi 3
1 PhD Student in Agricultural Economics, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Iran.
2 and Assistant Professor, Department of Agricultural Economics, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Iran
3 Assistant Professor, Department of Agricultural Economics, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Iran.
چکیده [English]

In today's world, water supply and demand management plays a pivotal role in organizing and planning the drinking water supply of urban and rural residents as well as the water supply of farmers and industrialists, especially in the current situation which all countries are facing the consequences of climate change. Therefore, in this study, the water demand of the agricultural sector of the Caspian littoral provinces was predicted by Markov-Switching method and compared with the Artificial Neural Network model using seasonal data for the period 2001: 1 to 2018: 4. Comparing the efficiency of water demand models estimated by Markov-Switching and ANN methods using Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) Showed that Markov-Switching approach was more efficient than water ANN models for predicting water demand. In addition, the forecast of agricultural water demand for both seasonal and annual periods was made for the periods of 2019: 1 to 2023: 4 and 2019 to 2023, respectively.

کلیدواژه‌ها [English]

  • Water Demand Prediction
  • Agriculture Sector
  • Markov-Switching
  • ANN
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