Applications of deep learning for phishing detection: a systematic literature review

C Catal, G Giray, B Tekinerdogan, S Kumar… - … and Information Systems, 2022 - Springer
Phishing attacks aim to steal confidential information using sophisticated methods,
techniques, and tools such as phishing through content injection, social engineering, online …

A review on the applications of machine learning for runoff modeling

B Mohammadi - Sustainable Water Resources Management, 2021 - Springer
The growing menace of global warming and restrictions on access to water in each region is
a huge threat to global hydrological sustainability. Hence, the perspective at which …

[HTML][HTML] Water quality prediction based on machine learning and comprehensive weighting methods

X Wang, Y Li, Q Qiao, A Tavares, Y Liang - Entropy, 2023 - mdpi.com
In the context of escalating global environmental concerns, the importance of preserving
water resources and upholding ecological equilibrium has become increasingly apparent …

An efficient data driven-based model for prediction of the total sediment load in rivers

R Noori, B Ghiasi, S Salehi, M Esmaeili Bidhendi… - Hydrology, 2022 - mdpi.com
Sediment load in fluvial systems is one of the critical factors sha** the river
geomorphological and hydraulic characteristics. A detailed understanding of the total …

A hybrid SVR-BO model for predicting the soil thermal conductivity with uncertainty

KQ Li, ZY Yin, Y Liu - Canadian Geotechnical Journal, 2023 - cdnsciencepub.com
This study proposes a generalised framework for develo** a hybrid machine learning
(ML) model that combines support vector regression (SVR) with hyperparameter …

Suspended sediment load prediction using long short-term memory neural network

N AlDahoul, Y Essam, P Kumar, AN Ahmed, M Sherif… - Scientific Reports, 2021 - nature.com
Rivers carry suspended sediments along with their flow. These sediments deposit at
different places depending on the discharge and course of the river. However, the …

Parameter identification of robot manipulators with unknown payloads using an improved chaotic sparrow search algorithm

X Li, J Gu, X Sun, J Li, S Tang - Applied Intelligence, 2022 - Springer
Parameter identification is essential for the model-based high-accuracy control of robot
manipulators. The objective of this work is to develop a swarm intelligence-based technique …

Modified Whale Optimization Algorithm based ANN: a novel predictive model for RO desalination plant

R Mahadeva, M Kumar, V Gupta, G Manik… - Scientific Reports, 2023 - nature.com
In recent decades, nature-inspired optimization methods have played a critical role in
hel** industrial plant designers to find superior solutions for process parameters …

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates …

H Gholami, A Mohammadifar, RD Behrooz… - Environmental …, 2024 - Elsevier
Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality,
climate, ecosystems and human health. Therefore, measurements, prediction and …

Suspended sediment load prediction modelling based on artificial intelligence methods: The tropical region as a case study

MF Allawi, SO Sulaiman, KN Sayl, M Sherif, A El-Shafie - Heliyon, 2023 - cell.com
The impact of the suspended sediment load (SSL) on environmental health, agricultural
operations, and water resources planning, is significant. The deposit of SSL restricts the …