Optimal mixture design for organic Rankine cycle using machine learning algorithm by Valerio Mariani, Saverio Ottaviano, Davide Scampamorte, Andrea De Pascale, Giulio Cazzoli, Lisa Branchini, Gian Marco Bianchi

“…Importantly, the targets and their respective weights within the objective function can be adjusted to meet the specific requirements of the application under analysis, making this approach adaptable to diverse research and industrial objectives. The algorithm is applied to a case study to demonstrate its ability to define a low-GWP blend that can replace HFC-134a in a micro-scale ORC with recuperator, while maintaining and potentially enhancing performance. …”
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Comparative Analysis of Optimization Algorithms to Enhance WPGSs Performance: Malaysia Case Study by Hussein Shutari, Taib Ibrahim, Nursyarizal Bin Mohd Nor, Hakim Abdulrab, Yahya Z. Alharthi, Mohammad Faridun Naim Tajuddin, Maveeya Baba

“…This outcome confirms the significant role of ODCSs in improving the efficiency and performance of WPGS under the mentioned challenges, while also revealing that their effectiveness varies depending on the precision of design established by the utilized optimization algorithm.…”
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MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design by Anoop Raghuvanshi, Abhinav Sharma, Abhishek Kumar Awasthi, Abhishek Sharma, Rahul Singhal, Kim Soon Chong, Sew Sun Tiang, Wei Hong Lim

“…This paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. …”
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Research on kd-tree Cache Optimization Based on Particle Index Sorting Algorithm by 张挺, 林震寰, 杨丁颖, 王宗锴, 陈轶凡

“…By calculating the dimension with the highest MAD value—thereby identifying the axis along which particle distribution exhibits the greatest variance—the algorithm ensures that particles with closer spatial proximity are assigned similar index values, thus optimizing data access during <italic>kd-tree</italic> searches. …”
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Elite Evolutionary Discrete Particle Swarm Optimization for Recommendation Systems by Shanxian Lin, Yifei Yang, Yuichi Nagata, Haichuan Yang

“…Traditional deep models are computationally expensive, while heuristic methods like particle swarm optimization struggle with discrete optimization. …”
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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach by Tomás de Jesús Mateo Sanguino, Jhon Carlos Mendoza Betancourt

“…To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. …”
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Optimization of strutted beam parameters by A. K. Yusupov, H. M. Musеlеmov, T. O. Ustarhanov

“…The objective of the research is to design strutted beams that have optimal parameters for metal consumption.Methods. …”
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Improved PESA algorithm based on comentropy by Kun WANG, Lin-lin WANG, Yan LIU, Yu-hua ZHANG, Meng WU

“…Aiming at the issue that the computational effort the complexity and the running time of PESA algorithm are increasing rapidly with the growth of the solutions set number, a comentropy-based PESA algorithm (C-PESA) by merg-ing the entropy value metric into PESA algorithm was proposed. …”
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GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation by Eman Mahmoud, Salem Alkhalaf, Tomonobu Senjyu, Masahiro Furukakoi, Ashraf Hemeida, Ghada Abozaid

“…However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. …”
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Optimizing Trajectories for Rechargeable Agricultural Robots in Greenhouse Climatic Sensing Using Deep Reinforcement Learning with Proximal Policy Optimization Algorithm by Ashraf Sharifi, Sara Migliorini, Davide Quaglia

“…In this paper, we propose a method based on Deep Reinforcement Learning enriched with a Proximal Policy Optimization (PPO) algorithm for determining the best trajectory an agricultural robot must follow to balance the number of measurements and autonomy adequately. …”
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Bio-inspired swarm intelligence for enhanced real-time aerial tracking: integrating whale optimization and grey wolf optimizer algorithms by GaoFeng Han

“…Abstract To address the decline in real-time tracking performance of moving targets in multi-UAV systems caused by uneven search coverage and low cooperation efficiency, the WGWO (Whale-Grey Wolf Optimization) model is proposed. The UAV swarm optimizes its flight paths using the spiral predation strategy of the WOA (Whale Optimization Algorithm) while employing a Kalman filter to process sensor data. …”
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Optimal sizing of battery energy storage system (BESS) for multiple applications using regression analysis and deep sleep optimizer algorithm by Chukwuemeka Emmanuel Okafor, Komla Agbenyo Folly

“…Regression analysis is used for mathematical formulations while Deep Sleep Heuristic algorithms in MATLAB environment is used for the optimization process for BESS optimal size. …”
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An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox by Chang Gao, Zhongqing Yu, Qiang Zhou

“…Comparing the performance of ACO-BP neural network algorithm and GA-ACO-BP algorithm， the results show that the convergence speed of ACO Optimized BP neural network is slow and the recognition accuracy is not high， while GA-ACO-BP algorithm can accurately and quickly diagnose and identify the fault of planetary gearbox.…”
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OPTIMAL LOSSES IN POWER DISTRIBUTION NETWORKS by M. I. Fursanov

“…The developed structural algorithm of technical losses of electricity in network 0,38–10 kV allows evaluating actual and optimal network loading, to determine minimum and reserves of losses enhancement, but it can be realize only when loading of lines and transformers is low. …”
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A Hybrid Whale Optimization Approach for Fast-Convergence Global Optimization by Athanasios Koulianos, Antonios Litke, Nikolaos K. Papadakis

“…In this paper, we introduce the Levy Flight-enhanced Whale Optimization Algorithm with Tabu Search elements (LWOATS), an innovative hybrid optimization approach that enhances the standard Whale Optimization Algorithm (WOA) with advanced local search techniques and elite solution management to improve performance on global optimization problems. …”
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Fuzzy Guiding of Roulette Selection in Evolutionary Algorithms by Krzysztof Pytel

“…The algorithm can be an effective tool in solving a wide range of optimization problems, for example, optimization of computer network infrastructure.…”
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Current-to-Best Crossover for Modified Jaya Algorithm by Sandeep Kumar Mogha, Sonal Deshwal, Pravesh Kumar

“…The Jaya algorithm is a recently designed metaheuristics and has been verified for its good performance in solving various engineering and scientific optimization applications. …”
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A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression by Tingkai Hou, Zonghong Zhou, Yonggang Zhang, Jing Zhang

“…Secondly, the DE-GWO, particle swarm optimization (PSO), genetic algorithm (GA), and SVR are integrated to identify the optimal superparameters, while the nonlinear mapping relationship between inversion parameters and displacements is established. …”
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