Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks by Amirhossein Taherpour (19273879)

“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”

Learning-Based Automatic Modulation Classification by Abdelmutalab, Ameen Elsiddig

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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …”
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LOCATING DAMAGES IN THIN ALUMINIUM PLATES USING LAMB WAVES AND AGENETIC OPTIMIZATION APPROACH by A. Masurkar, Faeez

“…A new damage localization method based on Lamb waves is presented here for thin aluminium (Al) plate specimens using a Genetic optimization (GO) approach. …”
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Mobile Energy Storage Systems for Benefit Maximization in Resilient Smart Grids by Alshaal, Dima

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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks by Mohamed Massaoudi (16888710)

“…<p dir="ltr">The transient power grid stability is greatly affected by the unpredictability of inverter-based resources of today's interconnected power grids. …”

The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability by Abd-El-barr, Mostafa

“…In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. …”
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Reputation-based cooperative detection model of selfish nodes in cluster-based QoS-OLSR protocol. (c2014) by Moati, Nadia

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Enhanced Microgrid Reliability Through Optimal Battery Energy Storage System Type and Sizing by Mohammadreza Gholami (17032317)

“…To determine the optimized size, a firefly optimization algorithm is used as an efficient meta-heuristic approach. …”

A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar (18560506)

“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”

Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

“…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …”
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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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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. …”

Four quadrant robust quick response optimally efficient inverterfed induction motor drive by Islam, S.M.

“…A model reference-based adaptive speed controller guarantees quick speed response and robustness of the drive system. …”
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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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An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan by Ghulam Abbas (764241)

“…In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). We designate the resulting algorithm as NEPFM-SSA as it took NEPFM’s Weibull distribution parameters as an initial guess and retuned them with the help of the simplex search algorithm to get updated Weibull distribution parameters, which ensure better fitting characteristics. …”

Resource Optimization for 3D Video SoftCast with Joint Texture/Depth Power Allocation by Saqr Khalil Saeed Thabet (19517560)

“…Then, a minimum distortion optimization algorithm iteratively computes all the possible resource allocations to find the optimal allocation based on the minimum distortion. …”

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…Next, principal component analysis (PCA) is used to select the best subset of attributes. After that, the optimized features are fed into single machine learning and stacking-based ensemble classifiers. …”

Bootstrap-based Aggregations and their Stability in Feature Selection by Salman, Reem Elfatih

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An Energy Efficient Wireless Sensor Network for Optimal Routing using Hybridized Bio-Inspired Technique by Askarovich, Ulashev Hubbim

“…While clustering techniques, such as Low Energy Adaptive Clustering Hierarchy (LEACH), help reduce energy usage, they suffer from inefficient local searches and poor exploration-exploitation balance.To address these limitations, this study proposes a hybrid bio-inspired optimization technique—Modified Harmony Search Algorithm (MHSA) combined with Competitive Swarm Optimization (CSO)—for optimal cluster head (CH) selection. …”
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