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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Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines by Haddad, Abdul Rahim

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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

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

TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. Initially, the features are grouped randomly to increase the probability of making them participating in the generation of different groups, and sorted based on their accuracy scores. …”

A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

“…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …”
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”

Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

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

“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”

Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System by Abu Zitar, Raed

“…It is believed that the evaluation of the outcomes of the course, based on grades, is necessary to improve the teaching and learning process. …”
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FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …”
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FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

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Enhancing fairness and scalability in IOTA tangle networks: a POMDP-based tip selection algorithm for decentralized systems by Mays Alshaikhli (22564811)

Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems by Amal Hichri (21383672)

Electrical efficiency of the photovoltaic/thermal collectors cooled by nanofluids: Machine learning simulation and optimization by evolutionary algorithm by Yan Cao (482880)

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

“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems by Faria Nawshin (21841598)

PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT by Khalil Assayed, Suha

“…The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. …”
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