A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

“…Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.…”
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Optimal Economic Modelling of Hybrid Combined Cooling, Heating, and Energy Storage System Based on Gravitational Search Algorithm-Random Forest Regression by Muhammad Shahzad Nazir, Sami ud Din, Wahab Ali Shah, Majid Ali, Ali Yousaf Kharal, Ahmad N. Abdalla, Padmanaban Sanjeevikumar

“…The random forest regression (RFR) model was optimized by the gravitational search algorithm (GSA). …”
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Techno-Economic Enhancement of Distribution Network by Optimal DG Allocation Along with Network Reconfiguration Considering Different Load Models and Levels by Chintan D. Patel, Tarun Kumar Tailor, Samyak S. Shah, Gulshan Sharma, Pitshou N. Bokoro

“…Therefore, this work focuses on improving DN performance with optimal DG integration along with NR. …”
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OPTIMIZATION PROBLEM FOR NUMBER OF LOGIC GATES NEEDED TO IMPLEMENT MULTIPLE BOOLEAN FUNCTIONS USING DECODER by M. Onai, H. Skopyk

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Enhancing Solid Oxide Fuel Cell Efficiency Through Advanced Model Identification Using Differential Evolutionary Mutation Fennec Fox Algorithm by Manish Kumar Singla, Jyoti Gupta, Ramesh Kumar, Pradeep Jangir, Mohamed Louzazni, Nimay Chandra Giri, Ahmed Jamal Abdullah Al-Gburi, E. I.-Sayed M. EI-Kenawy, Amal H. Alharbi

“…This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). …”
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Minimization of Material Waste Through Maintenance Interval Optimization in Transport Systems by Augustyn Lorenc, Małgorzata Kuźnar

“…Although the case study is based on railway vehicles, the approach is applicable to road, maritime, and air transport as well. By leveraging optimization algorithms, such as machine learning, this solution predicts optimal maintenance timing, thereby reducing resource consumption and improving operational efficiency. …”
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Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III by Mingzhang Pan, Xinxin Cao, Changcheng Fu, Shengyou Liao, Xiaorong Zhou, Wei Guan

“…Finally, based on the obtained mathematical model, the 3rd Non-dominated Sorting Genetic Algorithm (NGSA-III) is used to adjust and optimize the control parameters. …”
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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin Ab Rahman, Sakib Iqram Hamim

“…However, due to the limited battery capacity of sensor nodes, energy efficiency remains a critical challenge, especially since data transmission consumes the most energy. This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area by M. Sofiya, M. Arulmozhi

“…The Exhaustive Traffic Information Rate (ETIR) method evaluates the marginal rate of each feature, and the AntLion Behavior Optimization (ALBO) algorithm selects the most significant features, reducing dimensionality. …”
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Adaptive hybrid optimization for integrated project scheduling and staffing problem with time/resource trade-offs by Muhai Hu, Yao Wang, Wendi Tian

“…To solve this problem, we introduce an adaptive hybrid algorithm combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Demand side management with electric vehicles and optimal renewable resources integration under system uncertainties by Mohamed Mostafa Eissa, Rania Abdel Wahed Swief, Tarek Saad Abdel Salam

“…The study utilizes the Zebra optimization algorithm (ZOA), in comparison with the Whale optimization algorithm (WOA), Grey wolf optimization algorithm (GWO), and Genetic algorithm (GA). …”
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Enhanced Multi-Threshold Otsu Algorithm for Corn Seedling Band Centerline Extraction in Straw Row Grouping by Yuanyuan Liu, Yuxin Du, Kaipeng Zhang, Hong Yan, Zhiguo Wu, Jiaxin Zhang, Xin Tong, Junhui Chen, Fuxuan Li, Mengqi Liu, Yueyong Wang, Jun Wang

“…The method avoids premature convergence and improves population diversity by embedding the crossover mechanism of Differential Evolution (DE) into the Whale Optimization Algorithm (WOA) and introducing a vector disturbance strategy. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Abstract Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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Improvement of the Dynamic Response of Robust Sliding Mode MPPT Controller-Based PSO Algorithm for PV Systems under Fast-Changing Atmospheric Conditions by Dieudonné Marcel Djanssou, Abdouramani Dadjé, Ahmat Tom, Noël Djongyang

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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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Three-Layer Energy Optimization Strategy for CHP Microgrid Considering Path Loss by Kai LING, Can WANG, Gaorui ZHANG, Aoqi WANG, Sihu CHU, Fuyin TIAN, Xinran LI

“…The middle layer model improves the energy mutual aid ability between microgrids through barter and trading transactions and searches for the optimal transmission path for energy transactions between microgrids based on the Floyd-Warshall algorithm. …”
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Enhancing Route Optimization in Road Transport Systems Through Machine Learning: A Case Study of the Dakhla-Paris Corridor by Najib El Karkouri, Lahcen Hassine, Younes Ledmaoui, Hasna Chaibi, Rachid Saadane, Nourddine Enneya, Mohamed El Aroussi

“…However, these systems face numerous challenges, particularly regarding safety, cost, and route optimization, requiring innovative and practical solutions to improve their overall performance. …”
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OPTIMIZING PROCESSOR WORKLOADS AND SYSTEM EFFICIENCY THROUGH GAME-THEORETIC MODELS IN DISTRIBUTED SYSTEMS by Merlan Telmanov, Zukhra Abdiakhmetova, Amandyk Kartbayev

“…Key results from this study highlight that while Nash Equilibrium fosters stability within the system, the adoption of optimal cooperative strategies significantly improves operational efficiency and minimizes transaction costs. …”
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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

“…Wind power prediction (WPP) is necessary to the safe operation and economic dispatch of power systems. In order to improve the prediction accuracy of WPP, in this paper we propose a three-step model named SDAE-SVR-BA to be applied in short-term WPP based on stacked-denoising-autoencoder (SDAE) feature processing, bat algorithm (BA) optimization and support vector regression (SVR). …”
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Optimization method of building energy efficiency design based on decomposition multi objective and agent assisted model by Bai Chaoqin, Yang Zhuoyue

“…This study indicates that the improved multi-objective backbone particle swarm optimization algorithm relies on adaptive perturbation factors, with an average measured super volume of 29311 for one bedroom buildings and 49504 for three bedroom buildings. …”
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