Interpretable XGBoost-SHAP machine learning technique to predict the compressive strength of environment-friendly rice husk ash concrete
Author: Uddin, Md Nasir; Li, Ling-Zhi; Deng, Bo-Yu; Ye, Junhong
Early detection of adverse conditions in deep excavations using statistical process control
Author: Al Suwaidi, Dina; Haridy, Salah; Al Zaylaie, Marwan; Shamsuzzaman, Mohammad; Bashir, Hamdi; Maged, Ahmed; Arab, Mohamed G.
英文介紹
Innovative Infrastructure Solutions雜志英文介紹
Innovative Infrastructure Solutions is an international academic journal dedicated to the design, construction, and maintenance of innovative infrastructure. This magazine aims to promote interdisciplinary research and practice, covering fields such as civil engineering, transportation, water resource management, environmental protection, and sustainable development. By publishing original research papers, case studies, technical reports, and review articles.
The magazine provides a platform for academia, industry, and policy makers to share the latest research findings and innovative solutions. This journal emphasizes practical applications and technological innovation, encouraging the submission of research works that can improve infrastructure performance, reduce costs, extend lifespan, and reduce environmental impact. Through the peer review process, ensure that published research is of high quality and practical significance, thus becoming an important knowledge resource in the field of infrastructure.