Application of Classical Bird Swarm Learning Algorithm as a Method of Optimization in Nanotechnology Systems

Document Type : Articles

Authors

Faculty of Naval Aviation, Malek Ashtar University of Technology, Iran

Abstract

شکی نیست که فناوری نانو نقش عمده ای در
فناوری آینده ما خواهد داشت. علوم کامپیوتر فرصت های بیشتری برای
سیستم های کوانتومی و فناوری نانو فراهم می کند. تکنیک های محاسبات نرم مانند هوش انبوه ، می
توانند سیستم هایی با ویژگی های ظهور مطلوب را قادر سازند. بهینه سازی یک
فعالیت مهم و تعیین کننده در طراحی سازه است. نیاز ارزان در حافظه و
محاسبات با عوامل مستقل نانومتری که توانایی آنها ممکن است
توسط اندازه آنها محدود شود مناسب است. برای اعمال در کنترل نانوربات ، اصلاح الگوریتم PSO
مورد نیاز است. با استفاده از رفتار یادگیری شرطی سازی کلاسیک پرندگان در این مقاله ، ذرات
یاد می گیرند که یک رفتار طبیعی شرطی را نسبت به محرک بی قید و شرط انجام دهند.
ذرات موجود در فضای مسئله به چند دسته تقسیم می شوند و اگر ذره
ای تنوع رده خود را در سطح پایین پیدا کند ، سعی می کند به سمت بهترین
تجربه شخصی خود حرکت کند. ما همچنین از ایده حساسیت پرندگان به فضایی که
آنها در آن پرواز می کنند استفاده کردیم و سعی کردیم ذرات را در فضاهای نامناسب با سرعت بیشتری حرکت دهیم تا
از فضاها خارج شوند. برعکس ، ما سرعت ذرات را در
فضاهای ارزشمند کاهش می دهیم تا بیشتر جستجو کنیم. روش پیشنهادی در
نرم افزار MATLAB پیاده سازی شده و با نتایج مشابه مقایسه شده است. نشان داده شد که روش پیشنهادی
بدون توجه به عملکردهای غیر تعیین کننده یا
شرایط تصادفی ، راه حل خوبی برای مسئله پیدا می کند .

Keywords


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