نوع مقاله : مقاله پژوهشی لاتین
نویسندگان
1 دانشگاه فردوسی مشهد
2 دانشگاه بناب
چکیده
در این تحقیق یک مدل هیبریدی شبکه عصبی-GMDH جهت تخمین محتوای رطوبتی قطعات خربزه درختی در حین خشک‌شدن با هوای داغ در یک خشک‌کن کابینتی تعیین شد. برای این منظور پارامترهای زمان خشککردن، ضخامت قطعات و دمای خشککردن به‌عنوان ورودی تعریف گردید و مقدار نسبت رطوبتی (MR) به‌عنوان خروجی تخمین زده شد. دقیقاً 50 درصد داده‌ها جهت آموزش و 50 درصد دیگر برای تست کردن مدل استفاده شد. به‌علاوه، چهار مدل ریاضی مختلف بر داده‌های آزمایشگاهی برازش داده شدند و نتایج این مدل‌سازی با GMDH مقایسه گردید. مقدار ضریب تبیین (R2) و جذر میانگین مربعات خطا (RMSE) به‌دست آمده برای مدل GMDH به‌ترتیب 9960/0 و 0220/0 به‌دست آمد، درحالی‌که برای بهترین مدل ریاضی (مدل نیوتن) این مقادیر به‌ترتیب برابر 9954/0 و 0230/0 تعیین شد. پس می‌توان نتیجه گرفت که مدل‌سازی با GMDH کارایی بالاتری نسبت به مدل ریاضی در تخمین محتوای رطوبتی قطعات لایه نازک خربزه درختی دارد.
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