Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) by Kawash, Jalal Y.

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Second-order conic programming for data envelopment analysis models by Mourad, Nahia

“…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

“…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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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)

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

“…For this purpose, software quality prediction models have been extensively used. However, building accurate prediction models is hard due to the lack of data in the domain of software engineering. …”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
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Impact of AI and Dynamic Ensemble Techniques in Enhancing Healthcare Services: Opportunities and Ethical Challenges by Haseeb Javed (18576340)

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

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

“…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …”

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

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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by Mohamed Massaoudi (16888710)

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Analyzing the Influence of Climate and Anthropogenic Development on Vegetation Cover in the Coastal Ecosystems of GCC by Abhilash Dutta Roy (22466830)

“…We used Landsat satellite imagery and a Random Forest classification algorithm to map various land cover classes along the GCC coastline. …”

The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …”

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…<p dir="ltr">Pressure gradient (PG) in liquid-liquid flow is one of the key components to design an energy-efficient transportation system for wellbores. This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

“…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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