Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

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

Subjects:

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. …”

Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…Most such models are constructed using statistical or machine learning techniques. …”
Get full text
Get full text
Get full text

An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…Results Results show that our approach out-performs the machine learning algorithm C4.5 as well as random guessing. It also preserves the expressiveness of the models which provide not only the classification label but also guidelines to attain it. …”
Get full text
Get full text
Get full text

Public health utility of cause of death data: applying empirical algorithms to improve data quality by Sarah Charlotte Johnson (9715415)

Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
Get full text

A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

Get full text
Get full text

Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

Get full text

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”

Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

“…The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. …”

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”

A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading by Saoud A. Al-Janahi (18877213)

“…This paper studies the partial shading effect on one of Qatar’s most recent projects (metro stations), and models the Education City station, which is a major station. …”

Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

Get full text

Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. Combining statistical and ranking analyses confirms that the Levenberg–Marquardt (LM) is the most efficient optimization technique for training the MLPNN model. …”

Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

Graph Computing Systems and Partitioning Techniques: A Survey by Tewodros Alemu Ayall (19273717)

Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) by Kawash, Jalal Y.

Get full text
Get full text

An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

“…This research focuses on one of the most important aspects, which is uncertainty. The uncertainty aspect was not incorporated effectively in in the previous resource modeling models. …”
Get full text