Bee Colony Algorithm for Proctors Assignment. by Mansour, Nashat

“…We apply the Bee Colony algorithm to previously published data. …”
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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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Bee colony algorithm for assigning proctors to exams. (c2013) by Taha, Mohamad Kassem

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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. …”
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Optimizing Multi-Drone Flight Paths in Mountainous Terrain Using Enhanced Artificial Bee Colony and Genetic Algorithms by unknown

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POWER SYSTEM STABILIZER FOR MULTI-MACHINE POWER SYSTEMS BASED ON FUZZY LOGIC CONTROL AND ARTIFICIAL BEE COLONY ALGORITHM by unknown

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Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach by S. Punitha (17945654)

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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…Such data can be parsed using ML and AI approaches in designed to check attacks on CPSs. We present the new framework for the detection of cyberattacks, which makes use of AI and ML. …”
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Automating UML Models Refactoring using Search-Based Algorithms by unknown

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

“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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Quality estimation models optimization using genetic algorithms: Case of maintainability by Azar, D.

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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

“…The forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization algorithm. …”

Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Detecting Game Bugs Using Genetic Algorithms And Reachability Analysis Of Colored Petri Nets Models by unknown

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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. …”
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Valuation of commodity option prices under a regime-switching model with stochastic convenience yield: Model calibration using flower pollination optimization algorithm by A. Hamdi (17906918)

“…Using the WTI crude oil spot prices, the parameters involved in the proposed commodity regime-switching model are estimated by expectation–maximization algorithm. …”

Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms by Emara-Shabaik, Husam

“…In this paper, a modified genetic algorithm is used as a procedure to solve the parameter identification problem of the nonlinear Wiener-Hammerstein models. …”
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