ارائه یک مدل ترکیبی انعطاف‌پذیر برای پیش‌بینی قیمت محصولات کشاورزی؛ مطالعه موردی بازار گوشت ایران

اقتصاد و توسعه کشاورزی

مقاله 5، دوره 37، شماره 2 - شماره پیاپی 59، تیر 1402، صفحه 177-202   

نوع مقاله: مقالات پژوهشی به زبان انگلیسی

شناسه دیجیتال (DOI): 10.22067/jead.2023.82122.1187

نویسنده

رضا حیدری^*

موسسه پژوهش های برنامه ریزی، اقتصاد کشاورزی و توسعه روستایی

چکیده

موضوع قیمت یک عامل کلیدی در فعالیت مالی و تجاری مرتبط با بخش کشاورزی است، به گونه‌ای که همواره فعالان بخش کشاورزی در معرض ریسک‌های ناشی از نوسان قیمت محصولات کشاورزی قرار دارند. این مسئله نه تنها منجر به تصمیم‌گیری نادرست در زمینه تولید بهینه محصولات در سال جاری می‌شود، بلکه می‌تواند اجرای تعهدهای مالی آنان را در سال‌های آتی با خطر روبه‌رو سازد. در سال‌های اخیر، نوسانات قیمت محصولات کشاورزی در ایران افزایش یافته است و لذا پیش‌بینی دقیق تغییرات قیمت ضروری به نظر می‌رسد. در مطالعه حاضر، یک رویکرد ترکیبی انعطاف‌پذیر در پیش‌بینی قیمت ماهیانه گوشت گاو، گوشت گوسفند و مرغ از آوریل 2001 تا مارس 2021 ارائه شده است. در این روش جدید، سه روش ترکیب انفرادی مختلف شامل روش میانگین‌گیری، روش تنزیل ‌شده و روش انقباض برای ترکیب خروجی‌های پیش‌بینی مربوط به سه مدل ترکیبی متشکل از شبکه عصبی پرسپترون (MLPANN)  و الگوریتم‌های تکاملی (الگوریتم ژنتیک GA، الگوریتم ازدحام ذرات PSO و الگوریتم رقابت استعماری ICA) مورد استفاده قرار گرفتند. نتایج حاصل از این مطالعه نشان داد که بر اساس شاخص آماری RMSE، مدل ترکیبی پرسپترون- الگوریتم رقابت استعماری (MLPANN-GA) و روش انفرادی انقباضی با (K=0.25) دارای بالاترین دقت در پیش‌بینی قیمت گوشت گاو، گوسفند و مرغ است. همچنین عملکرد مدل پیشنهادی از اجزای آن (مدل‌های ترکیبی) بهتر است. روش پیشنهادی برای پیش‌بینی از نظر نوع محصول یا جایگزینی اجزای تشکیل‌دهنده دارای انعطاف‌پذیری است.

کلیدواژه‌ها

پیش‌بینی؛ قیمت محصولات کشاورزی؛ گوشت؛ مدل هیبریدی

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