Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm by Haitham ELwahsh, Ali Bakhiet, Omar Ibrahim Alirr, Tarek Khalifa, Maazen Alsabaan, Mohamed I. Ibrahem, Engy El-Shafeiy

“…It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. …”
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AI-based routing algorithms improve energy efficiency, latency, and data reliability in wireless sensor networks by Rahul Priyadarshi, Ravi Ranjan Kumar, Rakesh Ranjan, Padarti Vijaya Kumar

“…Abstract This paper proposes a modular Artificial Intelligence (AI)-based routing framework for Wireless Sensor Networks (WSNs) that integrates reinforcement learning (RL), supervised learning, and swarm intelligence techniques such as genetic algorithms (GA) and particle swarm optimization (PSO). …”
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Adaptive Reconfigurable Learning Algorithm for Robust Optimal Longitudinal Motion Control of Unmanned Aerial Vehicles by Omer Saleem, Aliha Tanveer, Jamshed Iqbal

“…This study presents the formulation and verification of a novel online adaptive reconfigurable learning control algorithm (RLCA) for improved longitudinal motion control and disturbance compensation in Unmanned Aerial Vehicles (UAVs). …”
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Management of large energy storage power plants: optimization of charging and discharging with cuckoo search algorithm by Behnam Motalebinejad, Majid Hosseina, Mojtaba Vahedi, Mahmoud Samiei Moghaddam

“…This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. …”
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DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots by Zhenpeng Zhang, Pengyu Li, Shanglei Chai, Yukang Cui, Yibin Tian

“…A multi-objective fitness function simultaneously optimizes path length, energy efficiency, and safety metrics, while genetic operators prevent algorithmic stagnation. …”
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QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems by Zuoqiang Du, Xingjie Li, Hui Li

“…Meanwhile, FJOSA employs a cross-layer optimization strategy that combines heuristic algorithms with cost functions to improve gate scheduling at a global level. …”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…The proposed model builds upon the UNET3 + architecture and integrates multi-scale feature extraction with enhanced optimization strategies to improve segmentation accuracy while significantly reducing computational complexity. …”
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Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study by Mahmoud B Almadhoun, MA Burhanuddin

“…This study aims to compare the effectiveness of machine learning (ML) algorithms in predicting prediabetes and identifying its key clinical predictors. …”
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Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

“…Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. …”
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Optimization of Table Tennis Swing Action Supported by the Temporal Convolutional Network Algorithm in Deep Learning by Shaoxuan Sun, Hongyu Zheng, Zhixin Lin

“…To enhance the navigation accuracy and interpretability of Unmanned Aerial Vehicles (UAVs) in sports analysis, this study proposes an improved model based on the Temporal Convolutional Network (TCN) algorithm, integrated with Explainable Artificial Intelligence. …”
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Optimizing convex hull discovery: Introducing a quintuple-region algorithm with enhanced computational efficiency by Fidan Nuriyeva, Hakan Kutucu

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A Chemistry-Based Optimization Algorithm for Quality of Service-Aware Multi-Cloud Service Compositions by Mona Aldakheel, Heba Kurdi

“…The experimental results demonstrated significant improvements over existing methods, such as Genetic Algorithms (GAs), Simulated Annealing (SA), and Tabu Search (TS), across multiple performance metrics, i.e., reductions of 14–33% are observed in combined clouds, while reductions of 20–85% are observed in examined clouds, and reductions of 74–98% are observed in examined services. …”
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A new intelligent control strategy for CSTH temperature regulation based on the starfish optimization algorithm by Davut Izci, Serdar Ekinci, Mostafa Jabari, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Ali Riza Yildiz, Seyedali Mirjalili

“…This study proposes a novel metaheuristic-driven control strategy, combining the two degrees of freedom-PID acceleration (2DOF-PIDA) controller with the recently developed starfish optimization algorithm (SFOA) for temperature control of the CSTH process. …”
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Optimizing Unmanned Vehicle Navigation: A Hybrid PSO-GWO Algorithm for Efficient Route Planning by Gökhan Altun, İlhan Aydın

“…In the hybrid algorithm, the simplicity and powerful global search capabilities of the Particle Swarm Optimization (PSO) algorithm are combined with the strong exploration and local minimum avoidance features of the Grey Wolf Optimization (GWO) algorithm. …”
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Exploring quantum control landscape and solution space complexity through optimization algorithms and dimensionality reduction by Haftu W. Fentaw, Steve Campbell, Simon Caton

“…Evaluations of traditional control techniques and machine learning algorithms reveal that Genetic Algorithms (GA) outperform Stochastic Gradient Descent (SGD), while Q-learning (QL) shows great promise compared to Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO). …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…The explored optimization algorithms include Adam, Adamax, AdamW, RMSprop, and SGD, while utilizing the EfficientNetB0, EfficientNetB3, EfficientNetB5, and EfficientNetB7 architectures. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…The explored optimization algorithms include Adam, Adamax, AdamW, RMSprop, and SGD, while utilizing the EfficientNetB0, EfficientNetB3, EfficientNetB5, and EfficientNetB7 architectures. …”
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…This study proposed the use of a support vector regression (SVR) predictive model improved by two metaheuristic algorithms used for optimization namely, Harris Hawks Optimization (HHO) and Particle Swarm Optimization (PSO) to predict chromatographic retention time of various food mycotoxin groups. …”
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State-of-the-Art Review: Models and Algorithms for Optimal Power System Design, Stabilization, and Reliability Enhancement by Senele Njabulo Zwane, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was utilized to systematically identify and refine the focus on the topic using the Scopus database, while VOSviewer assisted in analyzing trends. Noticeable aspect from the results includes the prevalence of metaheuristic algorithms like genetic algorithms, particle swarm optimization, cuckoo search, and various others. …”
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A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm by Pratap Singh, Nitin Mittal, Vikas Mittal, Tapankumar Trivedi, Ashish Singh, Szymon Łukasik, Rohit Salgotra

“…This work proposes a distributed cross-layer solution, leveraging the hybrid marine predator naked mole rat algorithm (MPNMRA) for MI-operated WUSNs. The solution, called DECMN (distributed energy-throughput efficient cross-layer network using MPNMRA), is designed to optimize the MI communication channels, MI relay coils (MI waveguide), and MI waveguide with 3D coils to fulfill quality of service (QoS) parameters, while achieving energy savings and throughput gains. …”
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