Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…Our research integrates a priori knowledge of threat zone locations, speeds, and directions with real-time data on the UAVs position relative to the threat zones to effectively manage dynamic threat zones, allowing UAVs to dynamically decide whether to navigate around or through these zones, thus significantly reducing trajectory costs. To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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Structure Design and Optimization of Self-locking Under-actuated Gripper by Shuting He, Yi Shen, Xianling Dai, Beibei Qiu, Xianfeng Pan, Mingxin Yuan

“…A structural parameter optimization model is established according to the balance of the clamping force of each gripper knuckle， and a genetic algorithm is introduced to realize the parameter optimization. …”
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Parameter Adaptive Manta Ray Foraging Optimization for Global Continuous Optimization Problems and Parameter Estimation of Solar Photovoltaic Models by Zhentao Tang, Kaiyu Wang, Yongxuan Yao, Mingxin Zhu, Lan Zhuang, Huiqin Chen, Jing Li, Li Yan, Shangce Gao

“…Furthermore, to enhance population diversity and avoid premature convergence, a randomly selected individual from the top $$ G $$ G high-quality solutions replaces the current best individual in the somersault foraging behavior. Based on these improvements, a parameter adaptive manta ray foraging optimization (PAMRFO) algorithm is developed. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Moreover, This study develops the proposed EffiXNet, a more refined version of EfficientNet augmented with self-attention mechanisms, dynamic convolutions, improved normalization methods, and Sparrow Search Optimization Algorithm for hyperparameter optimization. …”
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Wakeup strategy based on multi-objective optimization for fixed relay nodes by Xue-bin MA, Ai-li LI, Xiao-juan ZHANG

“…In order to deal with the “tidal effect” when people move in the city and solve the problem of high energy consumption of fixed relay nodes in opportunistic networks,a wakeup strategy of multi-objective optimization was proposed,which made use of the message forward ability and energy consumption of fixed relay nodes.This strategy used energy efficiency as the indicator to make the nodes awake,and deployed a network revenue-energy consumption model to resolve the contradiction between energy consumption and message forward ability.As the selection problem of awake relay nodes was a NP-hard problem,genetic algorithm was used to select proper fixed relay nodes to keep awake.In this process,selection operator was improved to make the algorithm converge to solution space quickly.Experiments show that the proposed wakeup strategy can guarantee the successful rate of message transmission and improve the average message forwarding capabilities of fixed relay nodes by consuming a unit energy.…”
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Automatic Generation Algorithm for Power Grid Diagram Based on Power Supply Area by Zhengwei JIANG, Lingyan QUE, Shuming SHA, Fengjian LIU, Xiangyang LIU

“…A mathematical model of station grid uniform diagram layout is built, and an improved force-directed grid layout algorithm is proposed for the supply area. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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Rock image classification based on improved EfficientNet by Kai Bai, Zhaoshuo Zhang, Siyi Jin, Shengsheng Dai

“…Second, the shuffle attention mechanism is integrated into the backbone network to enhance feature extraction while reducing model parameters. Finally, the Lion optimizer is employed to optimize the training process, improving both the accuracy and stability of the model. …”
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Optimized Application of CGA-SVM in Tight Reservoir Horizontal Well Production Prediction by Chao Wang, Ruogu Wang, Yuhan Lin, Jiafei Zhang, Xiaofei Xie, Zidan Zhao, Yunlin Xu

“…In this paper, chaotic genetic algorithm is used to optimize the traditional support vector machine, and the problems of slow convergence and local convergence are solved by chaotic genetic algorithm, and an improved support vector machine horizontal well production prediction method is established. …”
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A Mobile Wireless Sensor Coverage Optimization Method for Bridge Monitoring by Cong Mu, Jiguang Yang, Jiuyuan Huo

“…Aiming at the problem of resource allocation optimization of heterogeneous mobile wireless sensor (HMWS) networks in bridge structural health monitoring, this study proposes an enhanced coverage strategy for heterogeneous sensors based on an improved Hiking Optimization Algorithm (HOA). …”
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Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

“…On the other hand, Particle Swarm Optimization is a computational approach, an intelligent optimization, and the most popular algorithm that has been widely used for performing such types of optimization problems, which has faster convergence. …”
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Synchronous Remote Calibration for Electricity Meters: Application and Optimization by Zhiyong Zha, Hanfang Ge, Chengcheng Zou, Fei Long, Xingfeng He, Geng Wu, Chenxi Dong, Tianping Deng, Jiaxiang Xu

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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Feature selection is often used by some researchers to overcome these problems, because these methods have an important function in the process of reducing data dimensions and eliminating uncorrelated attributes that can cause noisy. Naive Bayes algorithm is used to support the process of determining the most optimal class. …”
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An Improved DeepSORT-Based Model for Multi-Target Tracking of Underwater Fish by Shengnan Liu, Jiapeng Zhang, Haojun Zheng, Cheng Qian, Shijing Liu

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Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique by Tran-Hieu Nguyen, Anh-Tuan Vu

“…A classification model based on the Adaptive Boosting algorithm is developed in order to eliminate unpromising candidates during the optimization process. …”
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Study on performance optimization for Chinese speech retrieval by ZHENG Tie-ran, HAN Ji-qing, LI Hai-yang

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A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

“…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

“…We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. …”
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Study on performance optimization for Chinese speech retrieval by ZHENG Tie-ran, HAN Ji-qing, LI Hai-yang

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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Then, these surrogate models with prior optimization knowledge are combined with the Expected Hypervolume Improvement (EHVI) acquisition function in a Bayesian optimization framework to efficiently discover Pareto-optimal configurations for the target task, which enables AutoCIL-FMOBO to jointly optimize key components, such as resampling methods, classifiers, and their hyperparameters, under a multi-objective setting. …”
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