Wind Forecasting in Railway Engineering /
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, mo...
| Main Authors: | , |
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| Format: | software, multimedia |
| Language: | eng |
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Amsterdam : Elsevier,
2021
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| Subjects: | |
| Online Access: | https://www.sciencedirect.com/science/book/9780128237069 |
| _version_ | 1796765051449769984 |
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| author | Liu, Hui, 1983- ScienceDirect (Online service) 7722 |
| author_facet | Liu, Hui, 1983- ScienceDirect (Online service) 7722 |
| author_sort | Liu, Hui, 1983- |
| collection | OCEAN |
| 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. |
| first_indexed | 2024-03-05T17:18:43Z |
| format | software, multimedia |
| id | KOHA-OAI-TEST:605941 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T17:18:43Z |
| publishDate | 2021 |
| publisher | Amsterdam : Elsevier, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:6059412023-10-08T08:00:37ZWind Forecasting in Railway Engineering / Liu, Hui, 1983- ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 Amsterdam : Elsevier,©20212021engWind 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.Includes bibliographical references and indexChapter 1. Introduction -- Chapter 2. Analysis of flow field characteristics along railways -- Chapter 3. Description of single-point wind time series along railways -- Chapter 4. Single-point wind forecasting methods based on deep learning -- Chapter 5. Single-point wind forecasting methods based on reinforcement learning -- 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.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.Railroad engineeringWind forecastingEngineering meteorologyhttps://www.sciencedirect.com/science/book/9780128237069URN:ISBN:9780128237069Remote access restricted to users with a valid UTM ID via VPN. |
| spellingShingle | Railroad engineering Wind forecasting Engineering meteorology Liu, Hui, 1983- ScienceDirect (Online service) 7722 Wind Forecasting in Railway Engineering / |
| title | Wind Forecasting in Railway Engineering / |
| title_full | Wind Forecasting in Railway Engineering / |
| title_fullStr | Wind Forecasting in Railway Engineering / |
| title_full_unstemmed | Wind Forecasting in Railway Engineering / |
| title_short | Wind Forecasting in Railway Engineering / |
| title_sort | wind forecasting in railway engineering |
| topic | Railroad engineering Wind forecasting Engineering meteorology |
| url | https://www.sciencedirect.com/science/book/9780128237069 |
| work_keys_str_mv | AT liuhui1983 windforecastinginrailwayengineering AT sciencedirectonlineservice7722 windforecastinginrailwayengineering |