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.
Part I Wind Anemometer Layout for Railways 2. Analysis of Flow Field Characteristics for Railways 3. Wind Anemometer Layout Optimization Methods for Railways
Part II Single-point Wind Forecasting for Railways 4. Description of Single-point Wind Time Series for Railways 5. Single-point Wind Forecasting Methods Based on Deep Learning 6. Single-point Wind Forecasting Methods for Railways Based on Reinforcement Learning 7. Single-point Wind Forecasting Methods for Railways Based on Ensemble Modelling
Part III Spatial Wind Forecasting for Railways 8. Description Methods of Spatial Wind for Railways 9. Data-driven Spatial Wind Forecasting Methods for Railways
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.