تخمین میزان محتوای رطوبتی میوه پاپایا با استفاده از سیستم تلفیقی عصبی-فازی و الگوریتم ژنتیک-شبکه عصبی

مجله پژوهشهای علوم و صنایع غذایی ایران

مقاله 3، دوره 12، شماره 6 - شماره پیاپی 42، بهمن و اسفند 1395، صفحه 767-779   

نوع مقاله: مقاله پژوهشی لاتین

شناسه دیجیتال (DOI): 10.22067/ifstrj.v12i6.62521

نویسنده

علیرضا یوسفی^*

فردوسی مشهد

چکیده

در این تحقیق از سیستم تلفیقی عصبی-فازی (ANFIS) و الگوریتم ژنتیک-شبکه عصبی (GA-ANN) برای مدل‌سازی سینتیک خشک شدن ورقه‌های پاپایا به‌وسیله هوای داغ استفاده گردید. ورودی‌های سیستم مدل‌سازی شامل سه ورودی زمان خشک شدن (320-0 دقیقه)، دمای خشک شدن (40، 50 و 60 درجه سانتی‌گراد) و ضخامت ورقه‌ها (3، 5 و 7 میلی‌متر) و خروجی سیستم شامل نسبت رطوبتی (MR) بود. در طراحی سیستم مدل‌سازی ANFIS از توابع عضویت مثلثی و 27 قانون استفاده گردید. نتایج نشان داد که داده‌های پیش‌بینی‌شده توسط سیستم ANFIS دارای تطبیق بالایی با نتایج آزمایشگاهی بود (R²= 0.9967, RMSE= 0.0161). همچنین سیستم مدل‌سازی GA-ANN بهینه‌شده، شامل 7 نرون در لایه مخفی، با دقت بالایی میزان رطوبت را پیش‌بینی نمود (R²= 0.9936, RMSE= 0.0220). ضریب انتشار مؤثر ورقه‌های پاپایا در بازه دمایی مورد آزمایش بین 6.93 ×10^-10 و 1.50 ×10^-09 مترمربع بر ثانیه تعیین شد. همچنین مقدار به‌دست آمده برای انرژی فعال‌سازی (32.5 کیلوژول بر مول) به‌خوبی تأثیر دمای خشک کردن بر روی ضریب انتشار را نشان داد.

کلیدواژه‌ها

سیستم تلفیقی عصبی-فازی؛ الگوریتم ژنتیک-شبکه عصبی؛ پاپایا

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