Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors by Sharaf, Omar Z.

“…Finally, using the developed design models and simulation algorithms, constrained non-linear multi-variable geometric optimization of the assembly components has been carried out to obtain minimum pumping power, maximum extractor heat transfer coefficient, and maximum thermoelectric power output. …”
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Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Wrapper-Based Feature Selection to Classify Flatfoot Disease by Casas-Ordaz, Angel

“…This task is considered from an optimization perspective, and the optimal subset is chosen using metaheuristic algorithms. …”
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Wrapper-Based Feature Selection to Classify Flatfoot Disease by Casas-Ordaz, Angel

“…This task is considered from an optimization perspective, and the optimal subset is chosen using metaheuristic algorithms. …”
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Autonomous Robot Navigation Based On Recurrent Neural Networks by Al-Sagban, Mariam Qusai

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AI-driven nonlinear optimization for knowledge extraction and pattern analysis in IoT-enabled data mining systems by Alimjon, Dadamuxamedov

“…In this paper, systematic exploration of the application of AI-based nonlinear optimization to elicit knowledge and pattern study in the IoT-enabled data mining takes place. …”
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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

“…The results demonstrate that the suggested RF-ANN-based technique can predict the optimal composite design with high accuracy (precision, recall, and f1-score for test and train dataset were 1). …”

A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

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Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach by Mohammad Taghi Dabiri (16904658)

“…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”

A cluster-based model for QoS-OLSR protocol by Otrok, Hadi

“…Therefore, we propose a novel clustering algorithm and a relay node selection based on different combinations of metrics, such as connectivity, residual energy, and bandwidth. …”
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Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier by JAIN, SWETA

“…The hyper parameters are optimized with DM optimization algorithm which improves the accuracy of classifier. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”

Hybridizing rule-based power system stabilizers with geneticalgorithms by Abido, M.A.

“…The proposed approach uses genetic algorithms (GA) to search for optimal settings of rule-based power system stabilizer (RBPSS) parameters. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

“…In addition to the deployment without requiring an explicit model of the plant, the simulation results demonstrate that the proposed solution modifies vehicle dynamics and maneuverability in most cases compared to the model-based conventional controller. Furthermore, the reduction in sideslip angle, excellent traction through minimizing tire slip ratio, avoiding oversteering and understeering, and maintaining an acceptable range of energy optimization are demonstrated for DRL controllers, especially for the TD3 and CL TD3 algorithms.…”

Artificial intelligence–empowered digital twins for simulation-driven security, privacy, and resiliency optimization in 6G networks by Senthilkumar, P.

“…In this survey, the Digital Twin frameworks based on AI are thoroughly revised in terms of improving the security, privacy, and resiliency of 6G networks, with a specific focus on Digital Twin modelling and prediction algorithms, such as, graph-based, temporal, and representation learning algorithms. …”
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Coordinated design of robust excitation and TCSC-based damping controllers by Abido, M.A.

“…The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. …”
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Improving multilayer perceptron neural network using two enhanced moth-flame optimizers to forecast iron ore prices by Ahmed, Basem

“…In this article, we propose two new optimization algorithms based on the moth-flame optimization algorithm (MFO), which mimics moths’ special navigation methods at night. …”
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Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach by El Gohary, Youssef Hesham

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