Enhanced Classification of Ear Disease Images Using Metaheuristic Feature Selection by Murat Ekinci, Furkancan Demircan, Zafer Cömert, Eyup Gedikli

“…The Whale Optimization Algorithm (WOA) effectively selected informative features for the k-Nearest Neighbors (kNN) model, achieving a classification accuracy of 92.6%. …”
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A novel approach for music genre identification using ZFNet, ELM, and modified electric eel foraging optimizer by Shuang Zhang, Zhiyong Sun, Hasan Jafari

“…Furthermore, the model incorporates a newly developed metaheuristic algorithm called the Modified Electric Eel Foraging Optimization (MEEFO) algorithm to optimize the ELM parameters and enhance overall performance. …”
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Convergence Study of Minimizing the Nonconvex Total Delay Using the Lane-Based Optimization Method for Signal-Controlled Junctions by C. K. Wong, Y. Y. Lee

“…A set of constraints is set up to ensure the feasibility and safety of the resultant optimized lane markings and signal settings. The main difficulty to solve this high-dimension nonlinear nonconvex delay minimization problem using cutting plane algorithm is the requirement of substantial computational efforts to reach a good-quality solution while approximating the nonlinear solution space. …”
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Optimizing drone-based pollination method by using efficient target detection and path planning for complex durian orchards by Ruipeng Tang, Jianxun Tang, Mohamad Sofian Abu Talip, Narendra Kumar Aridas, Binghong Guan

“…This study proposes an AI-powered drone-based pollination method for complex durian orchards, integrating improved object detection and optimized path planning. Specifically, we enhance the YOLO-v8 algorithm using the GhostNet lightweight network to reduce computational complexity while boosting detection precision. …”
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A Bio-Optimization Approach for Renewable Energy Management: The Case of a University Building in a Tropical Climate by Orlando Aguilar Pinzón, Orlando Aguilar Gallardo, Miguel Chen Austin

“…These findings highlight some of the challenges with integrating renewable energy systems into existing buildings while showcasing the potential of biomimetic algorithms, like the PSO and the GA, for targeted optimization tasks. …”
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Streamlined Model Predictive Control for a Triple-Optimization of Thermal Comfort, Heating Costs, and Photovoltaic Self-Consumption by Vukasin Klepic, Magdalena Wolf, Tobias Proll

“…Building on existing low-tech MPC developments, this study extends them to enhance PV self-consumption optimization. The proposed streamlined MPC algorithm relies solely on weather forecast data and real-time electricity market prices to determine the required heating power input. …”
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Mixed fleet-based two-echelon vehicle routing optimization for cold chain logistics with diverse recharging strategies. by Yaling Li, Wenzhu Liao, Yuqi Huang

“…The presented model optimizes economic and environmental considerations to mitigate air pollution and reduce dependence on non-renewable energy sources while providing feasible routes. …”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…The optimization approach under uncertainty provides robust predictive abilities across various scenarios, allowing the system to optimize energy management effectively, enhancing operational efficiency while minimizing overall energy losses, costs, and emissions. …”
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Optimization of Decision Support Technology for Offshore Oil Condition Monitoring with Carbon Neutrality as the Goal in the Enterprise Development Process. by Shiya Gao, Xin Guan, Xiaojing Cao, Zhili Bai, Caimeng Wang, Yun Zhan, Haiyang Yu

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Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter by Amar Rezoug, Jamshed Iqbal, Abdelkrim Nemra

“…The DRF-FG showed robustness in trajectory tracking compared to the controllers based on the Ant Lion Optimizer (DRF-A) and the Whale Optimization Algorithm (DRF-W). …”
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Integrated Carbon Flow Tracing and Topology Reconfiguration for Low-Carbon Optimal Dispatch in DG-Embedded Distribution Networks by Rao Fu, Guofeng Xia, Sining Hu, Yuhao Zhang, Handaoyuan Li, Jiachuan Shi

“…To efficiently solve this complex constrained model, a novel Q-learning enhanced Moth Flame Optimization (QMFO) algorithm was proposed. QMFO synergized the global search capability of the Moth Flame Optimization (MFO) algorithm with the adaptive decision-making of Q-learning, embedding an adaptive exploration strategy to significantly enhance solution efficiency and accuracy for multi-objective problems. …”
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A Deep Reinforcement Learning-Based Speed Optimization System to Reduce Fuel Consumption and Emissions for Smart Cities by Yıldıray Yiğit, Murat Karabatak

“…This method provides safer, more comfortable travel while lowering emissions and fuel consumption. Simulations with various scenarios prove the Deep Q-Network (DQN) algorithm’s success in adjusting speed according to traffic lights. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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Deep Reinforcement Learning-Enabled Trajectory and Bandwidth Allocation Optimization for UAV-Assisted Integrated Sensing and Covert Communication by Donghao Li, Binfang Du, Zhiquan Bai

“…The SAC-CC algorithm maximizes the CCTR by dynamically allocating bandwidth for sensing and communication tasks while adjusting the UAV’s trajectory to manage energy consumption. …”
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Analysis and mitigation of greenhouse gases by replacing traditional energy with a hybrid energy system using battery optimization by Madhusudhanan Sampath, Amalorpava Mary Rajee Samuel, Yamuna Devi M.M, Senthil Murugan

“…The paper presents an improved Lyapunov optimisation (LO) algorithm to optimally estimate the number of photovoltaic panels and battery banks for enhanced energy management. …”
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Chaotic chimp-mountain gazelle optimized FOPID control for frequency regulation in islanded airport microgrids with heterogeneous energy systems by Odelu P., Chandan Kumar Shiva, Sachidananda Sen, Vedik Basetti, Chandra Sekhar Reddy

“…Simulation results demonstrates that the CCMGO optimized fractional order proportional-integral-derivative controller exhibits better performances compared to the conventional genetic algorithm and particle swarm optimization based controllers, as well as contemporary metaheuristic algorithms like grey wolf optimizer and whale optimization algorithm. …”
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Balancing Human Mobility and Health Care Coverage in Sentinel Surveillance of Brazilian Indigenous Areas: Mathematical Optimization Approach by Juliane Fonseca Oliveira, Adriano O Vasconcelos, Andrêza L Alencar, Maria Célia S L Cunha, Izabel Marcilio, Manoel Barral-Netto, Pablo Ivan P Ramos

“…To optimize sentinel site selection, we implemented a linear optimization algorithm that maximizes (1) Indigenous region representation and (2) human mobility coverage. …”
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Adaptive Trajectory Optimization for UAV-IRS Systems in 6G Thz Networks Using Multi Agent-DRL by Elmadina Nahla Nur, Saeed Rashid A., Saeid Elsadig, Awouda Ala Eldin, Mujlid Hana M., Elshafie Hashim

“…Given the non-convex and NP-hard nature of the problem, traditional optimization methods are insufficient. To tackle this, we propose a Multi-Agent Deep Reinforcement Learning (MADRL) algorithm, which provides an efficient, low-complexity solution for trajectory optimization. …”
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Machinability Assessment and Multi-Objective Optimization of Graphene Nanoplatelets-Reinforced Aluminum Matrix Composite in Dry CNC Turning by Nikolaos A. Fountas, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

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Leveraging ensemble learning-based stock preselection with multiobjective investment optimization for stepwise decision-supported portfolio management by Jui-Sheng Chou, Tran-Bao-Quyen Pham

“…This stage leverages a newly developed algorithm tailored to address the expanded mean–variance problem, effectively decomposing and optimizing it while balancing multiple objectives. …”
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