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

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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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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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Improved Jaya Synergistic Swarm Optimization Algorithm to Optimize Task Scheduling Problems in Cloud Computing by Abualigah, Laith

“…The Jaya algorithm's ability to exploit the current best solutions is complemented by the SSO's collaborative search strategy, resulting in a synergistic optimization framework. …”
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Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

“…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …”
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Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties by AbdulGhafour, Husaen

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An exact and general model order reduction technique for the finite element solution of elastohydrodynamic lubrication problems by Habchi, W.

“…As such, it is exact and it preserves the generality of the solution scheme while reducing the size of its corresponding model and, consequently, the associated computational overhead. The technique is complemented with a splitting algorithm to alleviate the hurdle of solving an arising semidense matrix system. …”
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