Strong wind along the railways greatly affects the lateral stability of railway trains， even causes serious accidents such as derailment， overturning， etc. China， the United States， Japan and other countries have experienced severe wind-induced train overturning accidents ， causing serious loss of life and property. To ensure the safe operation of trains， it is urgently needed to enhance wind-proof performance of railway trains.In the existing railway wind engineering research， wind forecasting along the railways is recognized to be able to effectively improve the wind-proof performance of trains. The system based on wind forecasting can prevent the trains from being exposed to future strong wind to improve safety， and it can also avoid the redundant speed limitation of the trains to improve efficiency. Researchers have proposed several effective railway strong wind prediction systems.Due to the non-linearity and non-stationarity of the wind， it is still a difficult problem to realize high-precision spatio-temporal wind speed prediction. The author refines researches contents of the past 10 years， and completes this book. This book focuses on three key technologies， including anemometer layout， single-point wind prediction and spatial wind prediction. The characteristics of wind flow field， single-point wind， and spatial wind are analyzed. The advanced physical models and data-driven models are introduced with real data demonstration.
作者簡介
暫缺《鐵路工程風(fēng)預(yù)測（英文版）》作者簡介
圖書目錄
Chapter 1 Introduction 1．1 Overview of wind forecasting in train wind engineering 1．2 Typical scenarios of railway wind engineering 1．3 Key technical problems in wind signal processing 1．4 Wind forecasting technologies in railway wind engineering 1．5 Scope of this book References Chapter 2 Analysis of Flow Field Characteristics Along 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 References Chapter 3 Description of Single-Point Wind Time Series Along Railways 3．1 Introduction 3．2 Wind anemometer layout optimization methods along railways 3．3 Single-point wind speed-wind direction seasonal analysis 3．4 Single-point wind speed-wind direction heteroscedasticity analysis 3．5 Various single-point wind time series description algorithms 3．6 Description accuracy evaluation indicators 3．7 Summary and outlook References Chapter 4 Single-Point Wind Forecasting Methods Based on Deep Learning 4．1 Introduction 4．2 Wind data description 4．3 Single-point wind speed forecasting algorithm based on LSTM 4．4 Single-point wind speed forecasting algorithm based on GRU 4．5 Single-point wind speed direction algorithm based on Seriesnet 4．6 Summary and outlook References Chapter 5 Single-Point Wind Forecasting Methods Based on Reinforcement Learning 5．1 Introduction 5．2 Wind data description 5．3 Single-point wind speed forecasting algorithm based on Q-Iearning 5．4 Single-point wind speed forecasting algorithm based on deep reinforcement learning 5．5 Summary and outlook References …… Chapter 6 Single-Point Wind Forecasting Methods Based on Ensemble Modeling Chapter 7 Description Methods of Spatial Wind Along Railways Chapter 8 Data-Driven Spatial Wind Forecasting Methods Along Railways Nomenclature
鄂公網(wǎng)安備 42010302001612號(hào) 