Analysis of the factors affecting student performance using a neuro-fuzzy approach

M Abou Naaj, R Mehdi, EA Mohamed, M Nachouki - Education Sciences, 2023 - mdpi.com
Predicting students' academic performance and the factors that significantly influence it can
improve students' completion and graduation rates, as well as reduce attrition rates. In this …

A neuro-fuzzy model for predicting and analyzing student graduation performance in computing programs

R Mehdi, M Nachouki - Education and Information Technologies, 2023 - Springer
Predicting student's successful completion of academic programs and the features that
influence their performance can have a significant effect on improving students' completion …

The role of artificial intelligence in developing a banking risk index: an application of Adaptive Neural Network-Based Fuzzy Inference System (ANFIS)

IE Ahmed, R Mehdi, EA Mohamed - Artificial Intelligence Review, 2023 - Springer
Banking risk measurement and management remain one of many challenges for managers
and policymakers. This study contributes to the banking literature and practice in two ways …

Fuzzy rule-based and particle swarm optimisation MPPT techniques for a fuel cell stack

DN Luta, AK Raji - Energies, 2019 - mdpi.com
The negative environmental impact and the rapidly declining reserve of fossil fuel-based
energy sources for electricity generation is a big challenge to finding sustainable …

Impact of corporate performance on stock price predictions in the UAE markets: Neuro‐fuzzy model

EA Mohamed, IE Ahmed, R Mehdi… - Intelligent Systems in …, 2021 - Wiley Online Library
Predicting stock price remains one of the challenges for investors' investment strategies.
This study helps with accurate prediction and the main factors affecting variations in stock …

Comparing fuzzy rule-based MPPT techniques for fuel cell stack applications

DN Luta, AK Raji - Energy Procedia, 2019 - Elsevier
The process of maximum power extraction from alternative energy systems was at the first
instance applied to systems such as photovoltaic and wind power technologies. Both …

A distributed clustering algorithm guided by the base station to extend the lifetime of wireless sensor networks

AJ Yuste-Delgado, JC Cuevas-Martinez… - Sensors, 2020 - mdpi.com
Clustering algorithms are necessary in Wireless Sensor Networks to reduce the energy
consumption of the overall nodes. The decision of which nodes are the cluster heads (CHs) …

LEACH-FIS: an improved LEACH based on fuzzy inference system in MWSNs

Y Zhou, H Zhang, L Zhang, B Tang… - 2018 IEEE/CIC …, 2018 - ieeexplore.ieee.org
Hierarchical clustering is an effective method to save energy in immobile WSNs. In last
decade, with the mobility applications of WSNs increasing rapidly, hierarchical clustering of …

A novel approach to detect respiratory phases from pulmonary acoustic signals using normalised power spectral density and fuzzy inference system

R Palaniappan, K Sundaraj, S Sundaraj… - The clinical …, 2016 - Wiley Online Library
Background Monitoring respiration is important in several medical applications. One such
application is respiratory rate monitoring in patients with sleep apnoea. The respiratory rate …

A fuzzy neural approach for dynamic spectrum allocation in cognitive radio networks

GV Lakhekar, RG Roy - 2014 International Conference on …, 2014 - ieeexplore.ieee.org
In this paper, decision making scheme in cognitive radio is proposed by using fuzzy neural
system, due to which secondary users can utilizes the spectrum effectively with seamless …