Smart Metro Station Systems: Data Science and Engineering, Hui Liu (Professor, Director of Institute of Artificial Intelligence and Robotics (IAIR), and Vice-dean, School of Traffic and Transportation Engineering, Central South University, Changsha, China),Chao Chen (Scientist, Leader of Junior Research Group of Smart Environment, School of Traffic and Transportation Engineering, Central South University, Changsha, China),Yanfei Li (Associate Professor, Director of Smart Agriculture, College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China),Zhu Duan (Scientist, Leader of Junior Research Group of Smart Transportation, School of Traffic and Transportation Engineering, Central South University, Changsha, China),Ye Li (Scientist, Leader of Junior Research Group of Smart Robotics, School of Traffic and Transportation Engineering, Central South University, Changsha, China) (9780323905886) — Readings Books
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Smart Metro Station Systems: Data Science and Engineering
Paperback

Smart Metro Station Systems: Data Science and Engineering

Hui Liu (Professor, Director of Institute of Artificial Intelligence and Robotics (IAIR), and Vice-dean, School of Traffic and Transportation Engineering, Central South University, Changsha, China),Chao Chen (Scientist, Leader of Junior Research Group of Smart Environment, School of Traffic and Transportation Engineering, Central South University, Changsha, China),Yanfei Li (Associate Professor, Director of Smart Agriculture, College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China),Zhu Duan (Scientist, Leader of Junior Research Group of Smart Transportation, School of Traffic and Transportation Engineering, Central South University, Changsha, China),Ye Li (Scientist, Leader of Junior Research Group of Smart Robotics, School of Traffic and Transportation Engineering, Central South University, Changsha, China)
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Smart Metro Station Systems: Data Science and Engineering introduces key technologies in data science and engineering for smart metro station systems. The book consists of three main parts, focusing on the environment, people and energy. Each chapter includes practical applications, along with information on metro traffic flow monitoring and passenger guidance, methods for behavior analysis and trajectory projection, clustering and anomaly detection in crowd hotspots, monitoring and prediction for station humidity, monitoring and spatial prediction for air pollutants, time series feature extraction and analysis of metro load, characteristic and correlation analysis of metro load, and prediction and intelligent ventilation control.

This volume offers a key reference on the emerging area of smart metro stations and will be useful to those working on smart railways, data science, engineering, artificial intelligence and aligned fields.

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Format
Paperback
Publisher
Elsevier - Health Sciences Division
Country
United States
Date
24 January 2022
Pages
316
ISBN
9780323905886

Smart Metro Station Systems: Data Science and Engineering introduces key technologies in data science and engineering for smart metro station systems. The book consists of three main parts, focusing on the environment, people and energy. Each chapter includes practical applications, along with information on metro traffic flow monitoring and passenger guidance, methods for behavior analysis and trajectory projection, clustering and anomaly detection in crowd hotspots, monitoring and prediction for station humidity, monitoring and spatial prediction for air pollutants, time series feature extraction and analysis of metro load, characteristic and correlation analysis of metro load, and prediction and intelligent ventilation control.

This volume offers a key reference on the emerging area of smart metro stations and will be useful to those working on smart railways, data science, engineering, artificial intelligence and aligned fields.

Read More
Format
Paperback
Publisher
Elsevier - Health Sciences Division
Country
United States
Date
24 January 2022
Pages
316
ISBN
9780323905886

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