کاربست روش شبکه‌های عصبی در پیش‌بینی دمای سطح زمین، با استفاده از تصاویر حرارتی مادیس

فرحناز تقوی, عباس احمدی, زهرا زرگران

چکیده


در این مطالعه، مدلی ترکیبی از شبکه‌های عصبی ماژولار و پردازش تصاویر مادیس برای محاسبۀ دمای سطح زمین، در منطقه‌ای شامل شهر تهران، ارائه شده است. در این مدل، داده‌های تصاویر حرارتی با تکیه بر ویژگی‌های دمای درخشندگی در باندهای حرارتی 31 و 32 میکرومترسنجندۀ مادیس، به‌منزلۀ ورودی در شبکه‎های عصبی ماژولار به‌کار رفته و روش جدیدی براساس ترکیبی از شبکۀ عصبی نگاشت خودسازمانده و الگوریتم بهینه‌سازی تجمع ذرات پیشنهاد شد. نتایج به‌دست‌آمده نشان می‌دهد استفاده از این الگوریتم سبب توزیع مناسب داده‌های ورودی شبکه‌های عصبی می‌شود. در آخر، نتایج نهایی با مدل‌های شبکه‌های عصبی با آموزش و ساختار غیرماژولار نیز مقایسه شده است. نتایج این مقایسه نشان می‌دهد که زمان آموزش مدل در پیش‌بینی دمای سطح زمین کاهش، و دقت مدل افزایش یافته است. اختلاف کم بین مقادیر پیش‎بینی‌شده و مقادیر واقعی دما در منطقه نشان می‌دهد که دما با دقت مناسبی در این مدل پیش‌بینی شده است، به‌طوری‌که میانگین خطای مدل ترکیبی مقدار 0081/0 و درصد خطای مطلق نیز 59/10 است. 

واژگان کلیدی


تصاویر ماهواره، شبکۀ عصبی ماژولار، دمای سطح زمین.

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