[HTML][HTML] Prediction of the stability number of conventional rubble-mound breakwaters using machine learning algorithms

S Saha, S Changdar, S De - Journal of Ocean Engineering and Science, 2022 - Elsevier
An important issue in designing the structures of rubble-mound breakwaters, is to estimate
the stability number of its armor block. Most of the traditional stability analysis methods are …

A comparative study of machine learning classification for color-based safety vest detection on construction-site images

H Seong, H Son, C Kim - KSCE Journal of Civil Engineering, 2018 - Springer
Detecting the safety vests is an important foundation for various applications in safety
management and productivity measurement. The fluorescent yellow-green color and …

Particle Swarm Optimization based support vector machine for damage level prediction of non-reshaped berm breakwater

N Harish, S Mandal, S Rao, SG Patil - Applied Soft Computing, 2015 - Elsevier
The damage analysis of coastal structure is very much essential for better and safe design of
the structure. In the past, several researchers have carried out physical model studies on …

An application of machine learning algorithms on the prediction of the damage level of rubble-mound breakwaters

S Saha, S De, S Changdar - Journal of …, 2024 - asmedigitalcollection.asme.org
The stability analysis of breakwaters is very important to have a safe and economic design of
these coastal protective structures and the damage level is one of the most important …

Least squares support vector mechanics to predict the stability number of rubble-mound breakwaters

N Gedik - Water, 2018 - mdpi.com
In coastal engineering, empirical formulas grounded on experimental works regarding the
stability of breakwaters have been developed. In recent years, soft computing tools such as …

[HTML][HTML] Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

S Mandal, S Rao, N Harish - … Journal of Naval Architecture and Ocean …, 2012 - Elsevier
The damage analysis of coastal structure is very important as it involves many design
parameters to be considered for the better and safe design of structure. In the present study …

Supervised Machine Learning–Based Detection of Concrete Efflorescence

CL Fan, YJ Chung - Symmetry, 2022 - mdpi.com
The development of automated systems for detecting defects in and damage to buildings is
ongoing in the construction industry. Remaining aware of the surface conditions of buildings …

Stability assessment of rubble mound breakwaters using extreme learning machine models

X Wei, H Liu, X She, Y Lu, X Liu, S Mo - Journal of Marine Science and …, 2019 - mdpi.com
The stability number of a breakwater can determine the armor unit's weight, which is an
important parameter in the breakwater design process. In this paper, a novel and simple …

Parameter optimization using GA in SVM to predict damage level of non-reshaped berm breakwater

N Harish, N Lokesha, S Mandal… - … Journal of Ocean and …, 2014 - journals.sagepub.com
In the present study, Support Vector Machines (SVM) and hybrid of Genetic Algorithm (GA)
with SVM models are developed to predict the damage level of non-reshaped berm …

[PDF][PDF] Journal of Ocean Engineering and Science

S Saha, S Changdar, S De - 2022 - researchgate.net
abstract An important issue in designing the structures of rubble-mound breakwaters, is to
estimate the stability number of its armor block. Most of the traditional stability analysis …