Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models by Asan G. A. Muthalif (16888818)

On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

“…Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. …”

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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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)

Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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Graph Computing Systems and Partitioning Techniques: A Survey by Tewodros Alemu Ayall (19273717)

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A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators by Al-Hamouz, Z.M.

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A matrix-based damage assessment and recovery algorithm by Haraty, Ramzi A.

“…To make the process of damage assessment and recovery fast and effective (not scanning the entire log), researchers have proposed different methods for segmenting the log file, and accordingly presented different damage assessment and recovery algorithms. In this work we present efficient damage assessment and recovery algorithms to recover from malicious transactions in a database based on the concept of the matrix. …”
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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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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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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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A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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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. …”

Brain Source Localization in the Presence of Leadfield Perturbations by Momin, Rabiya Nakhat

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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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