Wind Forecasting in Railway Engineering

Wind Forecasting in Railway Engineering

1st Edition - June 17, 2021

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  • Author: Hui Liu
  • eBook ISBN: 9780128237076
  • Paperback ISBN: 9780128237069

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Description

Wind Forecasting in Railway Engineering presents core and leading-edge technologies in wind forecasting for railway engineering. The title brings together wind speed forecasting and railway wind engineering, offering solutions from both fields. Key technologies are presented, along with theories, modeling steps and comparative analyses of forecasting technologies. Each chapter presents case studies and applications, including typical applications and key issues, analysis of wind field characteristics, optimization methods for the placement of a wind anemometer, single-point time series along railways, deep learning algorithms on single-point wind forecasting, reinforcement learning algorithms, ensemble single-point wind forecasting methods, spatial wind, and data-driven spatial-temporal wind forecasting algorithms. This important book offers practical solutions for railway safety, by bringing together the latest technologies in wind speed forecasting and railway wind engineering into a single volume.

Key Features

  • Presents the core technologies and most advanced developments in wind forecasting for railway engineering
  • Gives case studies and experimental designs, demonstrating real-world applications
  • Introduces cutting-edge deep learning and reinforcement learning methods
  • Combines the latest thinking from wind engineering and railway engineering
  • Offers a complete solution to wind forecasting in railway engineering for the safety of running trains

Readership

Researchers in wind forecasting and railway engineering, engineering technicians, railway engineers, managerial staff in railway engineering; graduate researchers working in railway engineering, rail transit engineering, data science, and forecasting

Table of Contents

  • Chapter 1 Introduction
    1.1 Overview of wind forecasting in train wind engineering
    1.2 Typical applications of railway wind engineering
    1.2.1 Train overturning caused by wind
    1.2.2 Pantograph-catenary vibration caused by wind
    1.2.3 Bridge vibration caused by wind
    1.2.4 Wind-resistant railway yard design
    1.2.5 Wind-break wall design
    1.2.6 Other scenarios
    1.3 Key technical issues in wind signal processing
    1.3.1 Wind measurement technology
    1.3.2 Wind identification technology
    1.3.3 Wind forecasting technology
    1.3.4 Wind control technology
    1.4 Wind forecasting technologies in railway wind engineering
    1.4.1 Wind anemometer layout along railways
    1.4.2 Single-point wind forecasting along railways
    1.4.3 Spatial wind forecasting along railways
    1.5 Scope of this book
    1.6 References

    Part I Wind Anemometer Layout for Railways
    Chapter 2 Analysis of Flow Field Characteristics for Railways
    2.1 Introduction
    2.2 Analysis of spatial characteristics of railway flow field
    2.3 Analysis of seasonal characteristics of railway flow field
    2.4 Summary and outlook
    2.5 References

    Chapter 3 Wind Anemometer Layout Optimization Methods for Railways
    3.1 Introduction
    3.2 Layout optimization objective functions
    3.3 Single-objective wind anemometer layout optimization algorithm
    3.4 Multi-objective wind anemometer layout optimization algorithm
    3.5 Summary and outlook
    3.6 References

    Part II Single-point Wind Forecasting for Railways
    Chapter 4 Description of Single-point Wind Time Series for Railways
    4.1 Introduction
    4.2 Single-point wind speed - wind direction seasonal analysis
    4.3 Single-point wind speed - wind direction heteroscedasticity analysis
    4.4 Various single-point wind time series description algorithms
    4.5 Description accuracy evaluation indicators
    4.6 Summary and outlook
    4.7 References

    Chapter 5 Single-point Wind Forecasting Methods Based on Deep Learning
    5.1 Introduction
    5.2 Wind forecasting demand analysis and applications
    5.3 Single-point wind speed forecasting algorithm based on LSTM
    5.4 Single-point wind speed forecasting algorithm based on GRU
    5.5 Single-point wind speed direction algorithm based on Seriesnet
    5.6 Summary and outlook
    5.7 References

    Chapter 6 Single-point Wind Forecasting Methods for Railways Based on Reinforcement Learning
    6.1 Introduction
    6.2 Wind forecasting demand analysis and applicaitons
    6.3 Single-point wind speed forecasting algorithm based on Q-learning
    6.4 Single-point wind direction forecasting algorithm based on DDPG
    6.5 Summary and outlook
    6.6 References

    Chapter 7 Single-point Wind Forecasting Methods for Railways Based on Ensemble Modelling
    7.1 Introduction
    7.2 Wind forecasting demand analysis and applications
    7.3 Single-point wind speed forecasting algorithm based on multi-objective ensemble
    7.4 Single-point wind speed forecasting algorithm based on Stacking
    7.5 Single-point wind direction forecasting algorithm based on Boosting
    7.6 Summary and outlook
    7.7 References

    Part III Spatial Wind Forecasting for Railways
    Chapter 8 Description Methods of Spatial Wind for Railways
    8.1 Introduction
    8.2 Spatial wind correlation analysis
    8.3 Spatial wind spatial description based on WRF
    8.4 Description accuracy evaluation indicators
    8.5 Summary and outlook
    8.6 References

    Chapter 9 Data-driven Spatial Wind Forecasting Methods for Railways
    9.1 Introduction
    9.2 Wind forecasting demand analysis and applications
    9.3 Spatial wind forecasting algorithm based on statistical model
    9.4 Spatial wind forecasting algorithm based on intelligent model
    9.5 Spatial wind forecasting algorithm based on deep learning model
    9.6 Summary and outlook
    9.7 References

Product details

  • No. of pages: 362
  • Language: English
  • Copyright: © Elsevier 2021
  • Published: June 17, 2021
  • Imprint: Elsevier
  • eBook ISBN: 9780128237076
  • Paperback ISBN: 9780128237069

About the Author

Hui Liu

He holds joint PhD degrees from the Central South University and from Rostock University in Germany, and also obtained his habilation in Automation Engineering from the University of Rostock. He has published over 40 papers in leading journals, as well as two monographs. He holds 35 patents in China on transportation robotics and artificial intelligence, and has received numerous academic awards. He has extensive research and industry experience both in rail transit and in robotics.

Affiliations and Expertise

Professor of Robotics and Artificial Intelligence, and Vice-dean, Faculty of Transportation Engineering, Central South University, Changsha, China

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