کارایی شبکه عصبی مصنوعی در مدل سازی فرایند جذب یون سیانید از محلول آبی توسط نانوجاذب ZnO@MOF-199

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، گروه شیمی، دانشگاه آزاد اسلامی واحد اراک، اراک، ایران

2 استاد، گروه مهندسی شیمی و بیوشیمی، دانشگاه وسترن، لندن، کانادا

3 کارشناس ارشد، گروه شیمی، دانشگاه پیام نور، تهران، ایران

amnc.2021.9.36.4

چکیده

سیانید به عنوان محصول جانبی درپساب صنایع مختلفی وجود دارد که تصفیه آن قبل از ورود به محیط زیست الزامی است. سیانید را می توان با روش های مختلف فیزیکی، شیمیایی و بیولوژیکی از آب و پساب های صنعتی حذف کرد، اما اغلب این روش ها هزینه بر هستند. هدف از این مطالعه، بررسی کارایی شبکه عصبی مصنوعی ((ANN برای پیش بینی حذف یون سیانید موجود در محلول های آبی توسط نانو جاذبZnO@MOF-199 است. از نتایج آزمایشگاهی بدست آمده از پارامترهای مهم و تاثیر گذار بر فرایند حذف سیانید، شامل pH در محدوده (5 تا 9)، زمان تماس در محدوده (30-90 دقیقه) و دما در محدوده (25تا 45) درجه سانتی گراد برای مدل سازی شبکه های عصبی مصنوعی پسا انتشار خطا – لونبرگ مارکوارت (BP-LM) استفاده شد. در شبکه مذکور، پارامترهای ورودی از قبیل pH ، دما، زمان تماس، وزن جاذب و حجم نمونه به عنوان داده های ورودی و راندمان حذف سیانید به عنوان داده خروجی در نظر گرفته شد . برای مقایسه مدل های مختلف تدوین شده توسط شبکه عصبی مصنوعی از معیارهای آماری ضریب همبستگی و مجموع میانگین مربعات خطا استفاده شد. نتایج حاصل برای ضریب همبستگی و مجموع مربعات خطا با داشتن مقادیر 985/0 و65/0، بیانگر پیش بینی موفق شبکه در مدل سازی و کارایی شبکه عصبی مصنوعی در پیش بینی حذف یون سیانید از محلول می باشد.

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