طراحی سامانه سوناری با قابلیت دسته‌بندی اهداف فعال و غیرفعال آکوستیکی مبتنی بر شبکه‌ی عصبی فراابتکاری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه علوم دریایی امام خمینی (ره) نوشهر

2 دانشگاه علوم دریایی امام خمینی

چکیده

با توجه به اهمیت تعیین ماهیت اهداف سوناری در نبردهای دریایی، این مقاله به طراحی سامانه‌ای باقابلیت دسته­بندی اهداف سوناری فعال و غیرفعال با استفاده از شبکه­های عصبی پرسپترون چندلایه می‌پردازد. با توجه به نواقص پرسپترون­های چندلایه در کار با داده­های دنیای واقعی، این مقاله یک الگوریتم فرا ابتکاری جدید بانام بهینه‌ساز ازدحام ذرات با گروهای آشفته (CGPSO) را ارائه می­دهد. این الگوریتم با استفاده از گروه­های مجزای جستجو و همچنین نقشه­های آشفته فضای جستجو را بهتر و سریع­تر اکتشاف می­کند. به‌منظور ارزیابی سامانه طراحی‌شده، یک مجموعه داده سوناری مرجع، یک مجموعه داده آزمایشگاهی غیرفعال و یک مجموعه داده واقعی فعال توسعه داده شد. به‌منظور داشتن یک مقایسه جامع سامانه طراحی‌شده با بهینه‌سازهای معیار ازدحام ذرات (PSO)، جغرافیایی زیستی (BBO) و گرگ خاکستری (GWO) ازنظر سرعت همگرایی، دقت دسته‌بندی و قابلیت اعتماد مقایسه شد که سامانه طراحی‌شده نسبت به بهترین دسته­بندی کننده موجود، به­طور میانگین 33/2 درصد دقیق­تر عمل کرد.

کلیدواژه‌ها


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