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  1. طراحی و پیاده‌سازی سامانه‌های توصیه گر و تصمیم‌گیرنده بر اساس تحلیل داده‌های حجیم ترافیکی
طراحی و پیاده‌سازی سامانه‌های توصیه گر و تصمیم‌گیرنده بر اساس تحلیل داده‌های حجیم ترافیکی
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طراحی و پیاده‌سازی سامانه‌های توصیه گر و تصمیم‌گیرنده بر اساس تحلیل داده‌های حجیم ترافیکی

صفرپور، علیرضا Safarpour, Alireza

Design and Development of Recommendation & Decision Maker Systems Based on Massive Traffic Data Analysis

Safarpour, Alireza | 2021

566 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54503 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Gholampour, Iman; Karbasi, Mohammad
  7. Abstract:
  8. Data analysis is the science of extracting human-understandable knowledge from data. Massive data analysis is usually associated with the challenges of Volume, Velocity, Variety, Veracity and Value. These challenges are often referred to as 5V. With increasing processing power and reducing its cost in the last decade, massive data analysis methods have been used in various fields such as market, insurance and health, telecommunications and network, web search engines, intelligent transportation, etc. In this dissertation, we have tried to extract applied knowledge by using massive data analysis platforms and algorithms as well as traffic data. In this dissertation, a mathematical model for simulating urban traffic is presented by using traffic camera data and introducing the T-Rank algorithm implemented based on the PageRank algorithm which records an accuracy of 82% in estimating traffic parameters. Then, the hidden parameters involved in urban traffic are identified by using this mathematical model.The purpose of this dissertation is to review, design and implement appropriate hardware structures and software to create recommending and decision-making systems based on massive data analysis. The introduced hardware structure consists of a network of computers based on the Linux operating system and the processing of data that is available as large databases or data stream
  9. Keywords:
  10. Recommender System ; Smart City ; Intelligent Transportation System (ITS) ; Massive Data ; Data Analysis ; Traffic Data ; Decision Maker

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