A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

“…In addition, implementing feasible computational methods for such enormous data is by itself another challenge. …”
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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation by Abualigah, Laith

“…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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Teaching–learning-based optimization algorithm: analysis study and its application by Abualigah, Laith

“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

“…These techniques work well for bi-level thresholding, but when used to find the appropriate thresholds for multi-level thresholding, there will be issues with long calculation times, high computational costs, and the need for accuracy improvements. …”
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Design and implementation of a deep learning-empowered m-Health application by Akhan Akbulut (17380285)

Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting by AlSayegh, Hadeel Yacoub

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv... by Atif Iqbal (5504636)

“…Topology offers a reduced switch count solution with simple control strategy compared to the existing seven-level inverters. Different standard multicarrier sinusoidal pulse-width modulation techniques (SPWMs) are adapted for the generation of switching gate signals for the PUC power switches, and these SPWMs are compared with novel optimization-based selective harmonic elimination (SHE) that employs genetic algorithm (GA) for solving nonlinear SHE equation with a constraint that eliminated all third-order harmonics efficiently. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. A novel MH optimization algorithm, called arithmetic optimization algorithm (AOA), was proposed to address complex optimization tasks. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique by J. Jayapradha (21323774)

Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

“…Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. …”

Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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The Role of KM in Enhancing AI Algorithms and Systems by AlGhanem, Hani

“…The current study shows the relation between KM processes and AI systems from a higher perspective, giving different options to apply other KM processes for the same AI algorithm to reduce any implementation challenges and enhance the adoption level. …”
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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyper-parameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”

A State-of-the-Art Comprehensive Review on Maximum Power Tracking Algorithms for Photovoltaic Systems and New Technology of the Photovoltaic Applications by Ahmed Badawi (19757055)

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…While research in ASD diagnosis is evolving through the application of machine learning (ML) techniques, practical implementation in clinical settings has not progressed at the same pace. …”

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)