Enhanced fractional prediction scheme for effective matrix factorization in chaotic feedback recommender systems

ZA Khan, NI Chaudhary, TA Khan, U Farooq… - Chaos, Solitons & …, 2023 - Elsevier
The biggest wish of the e-commerce industry is to forecast and estimate the taste and
repugnance of users by utilizing user ratings for various products. Chaotic users' feedback …

[HTML][HTML] An innovative fractional order LMS algorithm for power signal parameter estimation

NI Chaudhary, R Latif, MAZ Raja… - Applied Mathematical …, 2020 - Elsevier
Parameter estimation is an important issue for the quality monitoring and reliability
assessment of power systems. In this study, an innovative fractional order least mean square …

Generalized fractional strategy for recommender systems with chaotic ratings behavior

ZA Khan, NI Chaudhary, MAZ Raja - Chaos, Solitons & Fractals, 2022 - Elsevier
To provide useful and accurate recommendations, the role of recommender systems for e-
commerce industry is to predict users' interest by approximating users' preferences and …

Generalized fractional optimization-based explainable lightweight CNN model for malaria disease classification

ZA Khan, M Waqar, MJAA Raja, NI Chaudhary… - Computers in Biology …, 2025 - Elsevier
Over the past few decades, machine learning and deep learning (DL) have incredibly
influenced a broader range of scientific disciplines. DL-based strategies have displayed …

RETRACTED ARTICLE: Fractional boundary element solution of three-temperature thermoelectric problems

MA Fahmy, MM Almehmadi, FM Al Subhi, A Sohail - Scientific Reports, 2022 - nature.com
The primary goal of this article is to propose a new fractional boundary element technique
for solving nonlinear three-temperature (3 T) thermoelectric problems. Analytical solution of …

Novel fractional swarming with key term separation for input nonlinear control autoregressive systems

F Altaf, CL Chang, NI Chaudhary, KM Cheema… - Fractal and …, 2022 - mdpi.com
In recent decades, fractional order calculus has become an important mathematical tool for
effectively solving complex problems through better modeling with the introduction of …

Brain-computer interface system based on p300 processing with convolutional neural network, novel speller, and low number of electrodes

JA Ramirez-Quintana, L Madrid-Herrera… - Cognitive …, 2021 - Springer
The P300 wave has been successfully employed to develop brain-computer interfaces (BCI)
for speller applications. However, methods to analyze the P300 require computers with high …

Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis

ZA Khan, M Waqar, NI Chaudhary, MJAA Raja, S Khan… - Heliyon, 2024 - cell.com
Alzheimer's is one of the brain syndromes that steadily affects the brain memory. The early
stage of Alzheimer's disease (AD) is referred to as mild cognitive impairment (MCI), and the …

Recommendation System for a Delivery Food Application Based on Number of Orders

CN Sánchez, J Domínguez-Soberanes, A Arreola… - Applied Sciences, 2023 - mdpi.com
With the recent growth in food-delivery applications, creating new recommendation systems
tailored to this platform is essential. State-of-the-art restaurant recommendation systems are …

Fractional-based stochastic gradient algorithms for time-delayed ARX models

T Xu, J Chen, Y Pu, L Guo - Circuits, Systems, and Signal Processing, 2022 - Springer
In this study, two fractional-based stochastic gradient (FSG) algorithms for time-delayed auto-
regressive exogenous (ARX) models are proposed. By combining momentum and adaptive …