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{ "item_title" : "Machine Learning for Transportation Research and Applications", "item_author" : [" Yinhai Wang", "Zhiyong Cui", "Ruimin Ke "], "item_description" : "Transportation is a combination of systems that presents a variety of challenges often too intricate to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle challenging transportation problems. This textbookis designed for college or graduate-level students in transportation or closely related fields to study and understand fundamentals in machine learning. Readers will learn how to develop and apply various types of machine learning models to transportation-related problems. Example applications include traffic sensing, data-quality control, traffic prediction, transportation asset management, traffic-system control and operations, and traffic-safety analysis.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/32/396/126/0323961266_b.jpg", "price_data" : { "retail_price" : "125.00", "online_price" : "125.00", "our_price" : "125.00", "club_price" : "125.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning for Transportation Research and Applications|Yinhai Wang

Machine Learning for Transportation Research and Applications

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Overview

Transportation is a combination of systems that presents a variety of challenges often too intricate to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle challenging transportation problems. This textbook
is designed for college or graduate-level students in transportation or closely related fields to study and understand fundamentals in machine learning. Readers will learn how to develop and apply various types of machine learning models to transportation-related problems. Example applications include traffic sensing, data-quality control, traffic prediction, transportation asset management, traffic-system control and operations, and traffic-safety analysis.

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Details

  • ISBN-13: 9780323961264
  • ISBN-10: 0323961266
  • Publisher: Elsevier
  • Publish Date: April 2023
  • Dimensions: 9 x 6 x 0.53 inches
  • Shipping Weight: 0.75 pounds
  • Page Count: 252

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