Machine learning prediction of mechanical properties of concrete: Critical review
Accurate prediction of the mechanical properties of concrete has been a concern since
these properties are often required by design codes. The emergence of new concrete …
these properties are often required by design codes. The emergence of new concrete …
Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
[HTML][HTML] Application of remote sensing and machine learning algorithms for forest fire map** in a Mediterranean area
Forest fire disaster is currently the subject of intense research worldwide. The development
of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
of accurate strategies to prevent potential impacts and minimize the occurrence of disastrous …
Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
DT Bui, P Tsangaratos, VT Nguyen, N Van Liem… - Catena, 2020 - Elsevier
The main objective of the current study was to introduce a Deep Learning Neural Network
(DLNN) model in landslide susceptibility assessments and compare its predictive …
(DLNN) model in landslide susceptibility assessments and compare its predictive …
Optimizing photovoltaic systems: a meta-optimization approach with GWO-Enhanced PSO algorithm for improving MPPT controllers
J Águila-León, C Vargas-Salgado, D Díaz-Bello… - Renewable Energy, 2024 - Elsevier
Environmental factors and load conditions influence the efficiency of power converters-key
elements in Photovoltaic (PV) systems. This study employs optimization algorithms to fine …
elements in Photovoltaic (PV) systems. This study employs optimization algorithms to fine …
Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility map** in Icheon, South Korea
Landslides are a geological hazard that can pose a serious threat to human health and the
environment of highlands or mountain slopes. Landslide susceptibility map** is an …
environment of highlands or mountain slopes. Landslide susceptibility map** is an …
[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility map**
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility map** (LSM) plays an …
of human life and property. As a result, landslide susceptibility map** (LSM) plays an …
[HTML][HTML] Predicting TBM penetration rate in hard rock condition: a comparative study among six XGB-based metaheuristic techniques
A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
Rainfall induced landslide studies in Indian Himalayan region: a critical review
Landslides are one of the most devastating and recurring natural disasters and have
affected several mountainous regions across the globe. The Indian Himalayan region is no …
affected several mountainous regions across the globe. The Indian Himalayan region is no …
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
With the increasing threat of recurring landslides, susceptibility maps are expected to play a
bigger role in promoting our understanding of future landslides and their magnitude. This …
bigger role in promoting our understanding of future landslides and their magnitude. This …