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Titlebook: Geo-Sustainnovation for Resilient Society; Select Proceedings o Hemanta Hazarika,Stuart Kenneth Haigh,Suman Manand Conference proceedings 2

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發(fā)表于 2025-3-21 17:11:00 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Geo-Sustainnovation for Resilient Society
副標(biāo)題Select Proceedings o
編輯Hemanta Hazarika,Stuart Kenneth Haigh,Suman Manand
視頻videohttp://file.papertrans.cn/384/383032/383032.mp4
概述Focuses on sustainability and innovations in design, construction and maintenance of geotechnical structures.Discusses technological advancement, challenges encountered and solutions for sustainable i
叢書(shū)名稱Lecture Notes in Civil Engineering
圖書(shū)封面Titlebook: Geo-Sustainnovation for Resilient Society; Select Proceedings o Hemanta Hazarika,Stuart Kenneth Haigh,Suman Manand Conference proceedings 2
描述.This book presents select proceedings of the 2nd International Conference on Construction Resources for Environmentally Sustainable Technologies (CREST 2023), and focuses on sustainability, promotion of new ideas and innovations in design, construction and maintenance of geotechnical structures with the aim of contributing towards climate change adaptation and disaster resiliency to meet the UN Sustainable Development Goals (SDGs). It presents latest research, information, technological advancement, practical challenges encountered, and solutions adopted in the field of geotechnical engineering for sustainable infrastructure towards climate change adaptation. This volume will be of interest to those in academia and industry alike..
出版日期Conference proceedings 2024
關(guān)鍵詞Sustainable Resources for Construction; Climate Change Adaptation; Geotechnical Engineering; Climate Ch
版次1
doihttps://doi.org/10.1007/978-981-99-9219-5
isbn_softcover978-981-99-9221-8
isbn_ebook978-981-99-9219-5Series ISSN 2366-2557 Series E-ISSN 2366-2565
issn_series 2366-2557
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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978-981-99-9221-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Die Fett verarbeitenden Industriendifferent appearance frequency of soils. So, it has characteristic of information bias. The purpose of this study is to propose a new idea of a global error function of Neural Networks (NNs) for stratigraphic classification estimation and its machine learning procedure in consideration with the info
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https://doi.org/10.1007/978-3-642-91377-8ive disaster, its scale and hazardous areas can be foreseen beforehand. Therefore, evacuating people from hazardous buildings to shelters in advance is an efficient effort to reduce casualties, but a scientific basis is still required. This paper proposes an approach for assessing each building’s ev
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Quellen-und Literaturverzeichnis,nd analysis of landslide hazards are very important for human, environmental, cultural, economic and social sustainability. This paper discusses the susceptibility of landslides and the regional dependence, in other words differences in characteristics between regions, based on ArcGIS and AI technol
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