Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
An insight of deep learning based demand forecasting in smart grids
JM Aguiar-Pérez, MÁ Pérez-Juárez - Sensors, 2023 - mdpi.com
Smart grids are able to forecast customers' consumption patterns, ie, their energy demand,
and consequently electricity can be transmitted after taking into account the expected …
and consequently electricity can be transmitted after taking into account the expected …
Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm
This study proposes different standalone models viz: Elman neural network (ENN), Boosted
Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As …
Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As …
Heat transfer and thermal conductivity of magneto micropolar fluid with thermal non-equilibrium condition passing through the vertical porous medium
N Ahmad Khan, M Sulaiman - Waves in Random and Complex …, 2022 - Taylor & Francis
This paper investigates the incompressible mixed convection flow of electrically conductive
micropolar fluid with a thermal non-equilibrium condition that passes through the vertical …
micropolar fluid with a thermal non-equilibrium condition that passes through the vertical …
A review on deep learning with focus on deep recurrent neural network for electricity forecasting in residential building
The rapid increase in urbanization has resulted in a significant rise in electricity
consumption, which resulted in a wide gap between the amount of electricity generated and …
consumption, which resulted in a wide gap between the amount of electricity generated and …
Model-based and model-free collision detection and identification for a parallel delta robot with uncertainties
PC Pham, YL Kuo - Control Engineering Practice, 2023 - Elsevier
This paper presents two methods for human collision detection and identification for a
parallel Delta robot considering uncertainties. In the model-based, a generalized momentum …
parallel Delta robot considering uncertainties. In the model-based, a generalized momentum …
Modeling the infiltration rate of wastewater infiltration basins considering water quality parameters using different artificial neural network techniques
Predicting the infiltration rate (IR) of treated wastewater (TWW) is essential in controlling
clogging problems. Most researchers that predict the IR using neural network models …
clogging problems. Most researchers that predict the IR using neural network models …
Comparing artificial neural network architectures for Brazilian stock market prediction
S Teixeira Zavadzki de Pauli, M Kleina… - Annals of Data Science, 2020 - Springer
Prediction of financial time series is a great challenge for statistical models. In general, the
stock market times series present high volatility due to its sensitivity to economic and political …
stock market times series present high volatility due to its sensitivity to economic and political …
Evaluation of water quality based on artificial intelligence: performance of multilayer perceptron neural networks and multiple linear regression versus water quality …
S Palabıyık, T Akkan - Environment, Development and Sustainability, 2024 - Springer
A significant problem in the sustainable management of water resources is the lack of
funding and long-term monitoring. Today, this problem has been greatly reduced by …
funding and long-term monitoring. Today, this problem has been greatly reduced by …
Combining homomorphic filtering and recurrent neural network in gait signal analysis for neurodegenerative diseases detection
M Saljuqi, P Ghaderyan - Biocybernetics and Biomedical Engineering, 2023 - Elsevier
Automatic, cost-effective, and reliable detection of neurodegenerative diseases (NDs) is one
of the important issues in clinical practice. The main idea of the proposed method in this …
of the important issues in clinical practice. The main idea of the proposed method in this …