نوع مقاله : مقاله پژوهشی

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 خشک شدن با هوای داغ در یک خشک کن کابینتی تعیین شد. برای این منظور پارامترهای زمان خشک کردن، ضخامت قطعات و دمای خشک‌کردن بعنوان ورودی تعریف گردید و مقدار نسبت رطوبتی (MR) به عنوان خروجی تخمین زده شد. دقیقاً 50 درصد داده‌ها جهت آموزش و 50 درصد دیگر برای تست کردن مدل استفاده شد. بعلاوه، 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) بدست آمده برای مدل GMDH به ترتیب  9960/0 و 0220/0 بدست آمد، در حالی که برای بهترین مدل ریاضی (مدل نیوتن) این مقادیر به ترتیب برابر 9954/0 و 0230/0 تعیین شد. پس می توان 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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