Zobrazeno 1 - 10
of 272
pro vyhledávání: '"Nhat-Duc Hoang"'
Autor:
Nhat-Duc Hoang
Publikováno v:
Mathematics, Vol 12, Iss 16, p 2542 (2024)
In recent years, the use of recycled aggregate (RA) in roller-compacted concrete (RCC) for pavement construction has been increasingly attractive due to various environmental and economic benefits. Early determination of the compressive strength (CS)
Externí odkaz:
https://doaj.org/article/f8fe3ddf16b14a5fa621cdc7678f24e5
Autor:
Nhat-Duc Hoang, Quoc-Lam Nguyen
Publikováno v:
Journal of Soft Computing in Civil Engineering, Vol 7, Iss 3, Pp 21-51 (2023)
The performance and serviceability of asphalt pavements have a direct influence on people's daily lives. Timely detection of pavement cracks is crucial in the task of periodic pavement survey. This paper proposes and verifies a novel computer vision-
Externí odkaz:
https://doaj.org/article/a145b944e1a2438a9a222f01de0cbad1
Autor:
Duc-Duy Ho, Jeong-Tae Kim, Nhat-Duc Hoang, Manh-Hung Tran, Ananta Man Singh Pradhan, Gia Toai Truong, Thanh-Canh Huynh
Publikováno v:
Buildings, Vol 14, Iss 6, p 1635 (2024)
Structural damage in the steel bridge anchorage, if not diagnosed early, could pose a severe risk of structural collapse. Previous studies have mainly focused on diagnosing prestress loss as a specific type of damage. This study is among the first fo
Externí odkaz:
https://doaj.org/article/5549cd310a28413ab0e5af036a0048e0
Publikováno v:
Mathematics, Vol 12, Iss 8, p 1267 (2024)
This study proposes a novel integration of the Extreme Gradient Boosting Machine (XGBoost) and Differential Flower Pollination (DFP) for constructing an intelligent method to predict the compressive strength (CS) of high-performance concrete (HPC) mi
Externí odkaz:
https://doaj.org/article/7f9d3d35e33942b996eefbec35caaaca
Autor:
Nhat-Duc Hoang, Van-Duc Tran
Publikováno v:
Journal of Soft Computing in Civil Engineering, Vol 7, Iss 1, Pp 114-134 (2023)
Manufactured sand has high potential for replacing natural sand and reducing the negative impact of the construction industry on the environment. This paper aims at developing a novel deep learning-based approach for estimating the compressive streng
Externí odkaz:
https://doaj.org/article/2b142971942a49e2a16cd667ab8addfc
Autor:
Alireza Arabameri, Subodh Chandra Pal, Romulus Costache, Asish Saha, Fatemeh Rezaie, Amir Seyed Danesh, Biswajeet Pradhan, Saro Lee, Nhat-Duc Hoang
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 12, Iss 1, Pp 469-498 (2021)
Spatial modelling of gully erosion at regional level is very relevant for local authorities to establish successful counter-measures and to change land-use planning. This work is exploring and researching the potential of a genetic algorithm-extreme
Externí odkaz:
https://doaj.org/article/09c9ba3100974df9b00a0d01674ea254
Publikováno v:
Advances in Civil Engineering, Vol 2022 (2022)
Pile foundations are widely used for high-rise structures constructed in soft ground. The bearing capacity of pile is a crucial parameter required during the design and construction phase of pile foundation engineering projects. In practice, accurate
Externí odkaz:
https://doaj.org/article/c016ce1822f8454180be4f82fcf9307c
Publikováno v:
Advances in Civil Engineering, Vol 2022 (2022)
During the phase of periodic survey, sealed crack and crack in asphalt pavement surface should be detected accurately. Moreover, the capability of identifying these two defects can help reduce the false-positive rate for pavement crack detection. Bec
Externí odkaz:
https://doaj.org/article/35f534163cd44d438995ff4c81360ae6
Autor:
Nhat-Duc Hoang
Publikováno v:
Mathematics, Vol 10, Iss 20, p 3771 (2022)
This paper aims at performing a comparative study to investigate the predictive capability of machine learning (ML) models used for estimating the compressive strength of self-compacting concrete (SCC). Seven prominent ML models, including deep neura
Externí odkaz:
https://doaj.org/article/f054ad564d684f5e959ba1ba572b9fb9
Publikováno v:
Applied and Environmental Soil Science, Vol 2021 (2021)
Soil erosion induced by rainfall under prevailing conditions is a prominent problem to farmers in tropical sloping lands of Northeast Vietnam. This study evaluates possibility of predicting erosion status by machine learning models, including fuzzy k
Externí odkaz:
https://doaj.org/article/0720739af0514948acc094c2b9241ece