تعيين ماشين¬هاي بردار پشتيبان بهينه در طبقه¬بندي تصاوير فرا طیفی بر مبناي الگوريتم ژنتيک
الموضوعات :
فرهاد صمدزادگان
1
(دانشگاه تهران)
حديثه سادات حسني
2
(دانشگاه تهران)
الکلمات المفتاحية: ماشین‌های بردار پشتيبان, تصاوير فرا طیفی, طبقه بندي, انتخاب مدل, انتخاب ويژگي, الگوريتم ژنتيک,
ملخص المقالة :
امروزه تصاوير فرا طیفی به علت غناي اطلاعات طيفي يک ابزار قوي و کارامد در سنجش از دور به حساب مي آيند و امکان تمايز بين عوارض مشابه را فراهم مي آورند. با توجه به پايداري ماشین‌های بردار پشتیبان در فضاهايي با ابعاد بالا، یک گزينه مناسب در طبقه بندي تصاوير فرا طیفی محسوب مي شوند. با اين وجود، عملکرد این طبقه بندي کننده ها تحت تأثیر پارامترها و فضاي ويژگي ورودي آن ها مي باشد. به منظور استفاده از ماشين هاي بردار پشتيبان با بيشترين کارایی، مي بايست مقادير بهينه ي پارامترها و همچنين زير مجموعه بهينه از ويژگي هاي ورودي تعيين گردند. در اين تحقيق از توانايي الگوريتم ژنتيک به عنوان يک تکنيک بهينه سازي فرا ابتکاري، در تعيين مقادير بهينه پارامترهاي ماشين هاي بردار پشتيبان و همچنين انتخاب زيرمجموعه ويژگي هاي بهينه در طبقه بندي تصاوير فرا طیفی استفاده شده است. نتايج عملي از به‌کارگیری روش فوق در خصوص داده هاي فرا طیفی سنجنده AVIRISنشان مي دهند، ويژگي هاي ورودي و پارامترها هر کدام جداگانه تأثیر بسزايي بر عملکرد ماشين هاي بردار پشتيبان دارند ولي بهترين عملکرد طبقه-بندي کننده با حل همزمان آن دو بدست مي آيد. در حل همزمان تعيين پارامتر و انتخاب ويژگي، براي کرنل گوسين و پلي نوميال به ترتيب 5% و 15% افزايش دقت با حذف بيش از نيمي از باندهاي تصوير حاصل شد. همچنين الگوريتم بهينه سازي شبيه سازي تبريد تدريجي به منظور مقايسه با الگوريتم ژنتيک پياده سازي شد که نتايج حاکي از برتري الگوريتم ژنتيک به ويژه با بزرگ و پيچيده شدن فضاي جستجو در رويکرد حل همزمان تعيين پارامتر و انتخاب ويژگي مي باشد.
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