Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Besides, we propose an improved equilibrium optimizer (EO) approach whereby the previous EO is modified. …”
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An Improved Crayfish Algorithm-Based Neural Network Method for Modeling Microstrip Patch Antennas by Shao-Long Cao, Yu Shao, Yang Wang, Ju Tan, Jie Zhang

“…This paper proposes an improved crayfish optimization algorithm (ICOA) to optimize the initial weights and biases of the neural network, aiming to enhance both convergence accuracy and speed. …”
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A Self-Adaptive Improved Slime Mold Algorithm for Multi-UAV Path Planning by Yuelin Ma, Zeren Zhang, Meng Yao, Guoliang Fan

“…The results show that AI-SMA improves the quality of optimal fitness by approximately <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>7.83</mn><mo>%</mo></mrow></semantics></math></inline-formula> over the original SMA while demonstrating superior robustness and effectiveness in generating collision-free trajectories.…”
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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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Combining 3-Opt and Improved Discrete Cuckoo Search Algorithm for the Traveling Salesman Problem by A. Sarucan, M. F. Berkaya

“…In terms of processing time, the average time of the proposed algorithm was 11.46 seconds, while the average time of the improved discrete CSA was 92.86 seconds. …”
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The Local Path Planning Algorithm for Amphibious Robots Based on an Improved Dynamic Window Approach by Xiaoqiang Dai, Chengye Liu, Qiang Lai, Xin Huang, Qingjun Zeng, Ming Liu

“…The speed resolution adaptive adjustment algorithm improves the ability to pass through a complex multiple-obstacle area, and the dynamic obstacle prediction algorithm optimizes obstacle avoidance paths. …”
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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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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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Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox by Chang Gao, Zhongqing Yu, Qiang Zhou

“…Aiming at the problems of low fault recognition rate， slow convergence speed and difficult parameter selection in the process of fault diagnosis of planetary gearbox based on BP neural network improved by optimization algorithm， a GA-ACO algorithm is proposed to optimize the parameters of neural network. …”
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An Improved KF-RBF Based Estimation Algorithm for Coverage Control with Unknown Density Function by Lei Zuo, Maode Yan, Yaoren Guo, Wenrui Ma

“…Compared with the other estimation algorithms, a novel sampling regulation mechanism is designed to improve the estimation performance and reduce the computational load. …”
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Recognition algorithm of piano playing music notes based on improved hidden Markov model by Ziwei Wang

“…The recognition process of piano playing music notes is affected by low-frequency components, resulting in suboptimal features that affect recognition accuracy. Therefore, an improved hidden Markov model based recognition algorithm for piano playing music notes is proposed. …”
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An improved sliding mode observer algorithm for PMSM based on deformable fuzzy neural network by Xiaolin Li, Na Liu, Juan Song, Yiyan Zhang

“…The findings suggest that the proposed algorithm enhances the accuracy of speed estimation and rotor position while optimizing the speed control performance of vector control system.…”
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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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Path Planning for Construction Robot Based on the Improved A* Algorithm and Building Information Modeling by Dejiang Wang, Bolong Liu, Haili Jiang, Panpan Liu

“…Finally, the improved A* algorithm is employed to perform path planning within the environment map generated from the BIM model, resulting in the generation of the optimal path. …”
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BDCOA: Wavefront Aberration Compensation Using Improved Swarm Intelligence for FSO Communication by Suhas Shankarnahalli Krishnegowda, Arvind Kumar Ganesh, Parameshachari Bidare Divakarachari, Veena Yadav Shankarappa, Nijaguna Gollara Siddappa

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An efficient swarm evolution algorithm with probability learning for the black and white coloring problem by Zhiqiang Zhang, Li Zhang, Xiujun Zhang

“…Furthermore, crossover operation, perturbation operation, and tabu search strategy improve the search ability of the algorithm, while evolutionary operation with probability learning mechanism increases the probability of the algorithm finding better solutions. …”
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Optimized planning of electric vehicle charging infrastructure for grid performance improvement by Mohammad Reza Maghami, Ka Fei Thang, Arthur G. O. Mutambara, Ali Akbar Firoozi, Elnaz Yaghoubi, Mehdi Zareian Jahromi, Elaheh Yaghoubi

“…This paper presents a multi-objective optimization framework developed using particle swarm optimization (PSO) algorithm to determine optimal placement and capacity of EV charging infrastructures. …”
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

“… This research aimed to automate the fitting of kinetic models using genetic algorithms (GAs) to optimize the estimation of kinetic parameters—the reaction rate constant (k) and the initial value of total titratable acidity (TTA, C₀)—and enhance predictive accuracy. …”
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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
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Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model by Hewu Kuang

“…The genetic algorithm is improved by immune cloning algorithm, and the CGA-BP neural network model is established to obtain the global optimal solution. …”
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