Zhu Duan – författare

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.

Presents relevant core technologies of data science and engineering in smart metro station systems Describes systems based on holographic perception, terminal platform control and highly-autonomous operation Gives a large number of practical case studies and experimental designs Introduces state-of-the-art machine learning and data mining methods for smart metro station systems Offers a comprehensive, up-to-date research solution for the emerging area of smart metro stations

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.- Presents relevant core technologies of data science and engineering in smart metro station systems- Describes systems based on holographic perception, terminal platform control and highly-autonomous operation- Gives a large number of practical case studies and experimental designs- Introduces state-of-the-art machine learning and data mining methods for smart metro station systems- Offers a comprehensive, up-to-date research solution for the emerging area of smart metro stations

This book presents a series of state-of-the-art methods for air quality monitoring in various engineering environment by using data science. The book can be used for students, engineers, scientists and managers in the fields of environmental engineering, atmospheric science, urban climate, civil engineering, traffic and vehicle engineering, etc.

This book presents a series of state-of-the-art methods for air quality monitoring in various engineering environment by using data science. In the book, the data-driven key techniques of the preprocessing, decomposition, identification, clustering, forecasting and interpolation of the air quality monitoring are explained in details with lots of experimental simulation. The book can provide important reference for the development of data science technologies in engineering air quality monitoring. The book can be used for students, engineers, scientists and managers in the fields of environmental engineering, atmospheric science, urban climate, civil engineering, traffic and vehicle engineering, etc.