پایان نامه ارائه‌ چارچوبی در راستای بهبود پیش‌ بینی وضعیت ترافیک

فهرست:

فصل اول. مقدمه

1-1- تعریف مسئله..................................................................................................................................... 2

1-2- چالش‌های مسئله.............................................................................................................................. 4

1-3- نگاهی به فصول پایان­نامه................................................................................................................ 7

فصل دوم. مبانی نظری تحقیق

2-1- مقدمه............................................................................................................................................... 10

2-2- متدهای یادگیری تجمعی............................................................................................................ 11

2-2-1- تعاریف مفاهیم اولیه..................................................................................................... 11

2-2-2- درخت بوستینگ........................................................................................................... 13

2-2-3- درخت بگینگ................................................................................................................ 13

2-3- رندوم فارست.................................................................................................................................. 15

2-3-1- مراحل توسعه‌ی رندوم فارست.................................................................................. 16

2-3-2- تئوری‌های مرتبط با رندوم فارست........................................................................... 19

2-3-3- رندوم فارست برای رگرسیون..................................................................................... 22

2-3-4- مزایا و کاربردهای رندوم فارست................................................................................ 23

2-4- نتیجه­گیری..................................................................................................................................... 24

فصل سوم. پیشینه تحقیق

3-1- مقدمه............................................................................................................................................... 26

3-2- تعریف مسئله.................................................................................................................................. 26

3-3- روش‌های مبتنی بر آنالیزهای سری زمانی............................................................................. 29

3-4- روش‌های مبتنی بر مدل‌های شبکه عصبی............................................................................ 32

3-5- روش‌های مبتنی بر الگوریتم‌های داده­کاوی........................................................................... 34

فصل چهارم. معرفی تکنیک پیشنهادی

4-1- مقدمه............................................................................................................................................... 40

4-2- خصوصیات کلی پایگاه داده........................................................................................................ 41

4-3- پایگاه داده­ی مورد استفاده.......................................................................................................... 42

4-3-1- داده‌ی آموزشی............................................................................................................... 44

4-3-2- داده‌ی آزمایشی.............................................................................................................. 44

4-4- تکنیک پیشنهادی......................................................................................................................... 45

4-4-1- بررسی توزیع جریان‌های ترافیکی............................................................................. 47

4-4-2- مرحله پیش پردازش و استخراج ویژگی.................................................................. 50

4-4-3- مرحله شناسایی و تقسیم بندی به Context های مختلف................................ 52

4-4-4- مرحله یادگیری با بکارگیری Context-Aware Random Forest.................. 56

فصل پنجم. نتایج تجربی

5-1- مقدمه............................................................................................................................................... 59

5-2- پایگاه داده........................................................................................................................................ 60

5-3- معیارهای ارزیابی........................................................................................................................... 61

5-3-1- معیار ارزیابی خطای پیش­بینی.................................................................................. 61

5-3-2- مقایسه کارآیی معیارهای سنجش فاصله بر روی مشاهدات ترافیکی.............. 62

5-4- بررسی تناسب الگوریتم رندوم فارست در مقایسه با دیگر متدها.................................... 64

5-5- تنظیمات اعمال شده در پیاده سازی الگوریتم (تنظیم پارامترها)................................... 66

5-6- ارزیابی سایز گردآمدگی بر روی داده‌ی اعتبارسنجی.......................................................... 67

5-7- استخراج مجموعه‌های نمونه‌های آموزشی.............................................................................. 70

5-8- نتایج یادگیری الگوریتم بر روی مجموعه‌های نمونه‌های آموزشی.................................... 72

فصل ششم. نتیجه‌گیری

خلاصه­ی مطالب و نتیجه­ گیری............................................................................................................ 75

فهرست منابع و مآخذ.......................................................................................................................... 78

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