Machine learning prediction of mechanical properties of concrete: Critical review

WB Chaabene, M Flah, ML Nehdi - Construction and Building Materials, 2020 - Elsevier
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 …

Rainfall induced landslide studies in Indian Himalayan region: a critical review

A Dikshit, R Sarkar, B Pradhan, S Segoni, AM Alamri - Applied Sciences, 2020 - mdpi.com
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 …

[HTML][HTML] Application of remote sensing and machine learning algorithms for forest fire map** in a Mediterranean area

M Mohajane, R Costache, F Karimi, QB Pham… - Ecological …, 2021 - Elsevier
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 …

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 …

[HTML][HTML] Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

J Zhou, Y Qiu, DJ Armaghani, W Zhang, C Li, S Zhu… - Geoscience …, 2021 - Elsevier
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 …

Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility map** in Icheon, South Korea

WL Hakim, F Rezaie, AS Nur, M Panahi… - Journal of environmental …, 2022 - Elsevier
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 …

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 …

[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility map**

L Lv, T Chen, J Dou, A Plaza - … Journal of Applied Earth Observation and …, 2022 - Elsevier
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 …

A spatially explicit deep learning neural network model for the prediction of landslide susceptibility

D Van Dao, A Jaafari, M Bayat, D Mafi-Gholami, C Qi… - Catena, 2020 - Elsevier
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 …

[Retracted] Taxonomy of Adaptive Neuro‐Fuzzy Inference System in Modern Engineering Sciences

S Chopra, G Dhiman, A Sharma… - Computational …, 2021 - Wiley Online Library
Adaptive Neuro‐Fuzzy Inference System (ANFIS) blends advantages of both Artificial Neural
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …