شبکه عصبی فازی مین- ماکس چندسطحی با باکس‌های وزن‌دار
الموضوعات :رضا داوطلب 1 , محمدعلی بالافر 2 , محمدرضا فیضی درخشی 3
1 - دانشگاه تبریز
2 - دانشگاه تبریز
3 - دانشگاه تبریز
الکلمات المفتاحية: طبقه‌بندی شبکه عصبی فازی مین- ماکس یادگیری ماشین وزن‌دار,
ملخص المقالة :
در این مقاله شبکه عصبی فازی مین- ماکس چندسطحی با باکس‌های وزن‌دار (WL-FMM) برای استفاده در کلاس‌بندی ارائه می‌گردد که یک ابزار یادگیری با نظارت بسیار سریع بوده و قادر به یادگیری داده‌ها به صورت برخط و تک‌گذار است. در این روش برای حل مشکل نواحی همپوشان که از مشکلات همیشگی روش‌های فازی مین- ماکس بوده، از باکس‌هایی با اندازه کوچک‌تر و وزن بیشتر استفاده می‌شود. این کار باعث افزایش دقت طبقه‌بندی شبکه در نواحی مرزی نمونه‌ها می‌گردد. همچنین با توجه به تغییراتی که در ساختار الگوریتم داده شده و بر اساس نتایج آزمایشی به دست آمده، روش ارائه‌شده نسبت به روش‌های مشابه از پیچیدگی زمانی و مکانی کمتری برخوردار بوده و نسبت به پارامترهایی که از طرف کاربر مشخص می‌شود، حساسیت کمتری دارد.
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