Improved Aerial Surface Floating Object Detection and Classification Recognition Algorithm Based on YOLOv8n by Lili Song, Haixin Deng, Jianfeng Han, Xiongwei Gao

“…To address the aforementioned challenges, we proposed an improved YOLOv8-HSH algorithm based on YOLOv8n. The proposed algorithm introduces several key enhancements: (1) an enhanced HorBlock module to facilitate multi-gradient and multi-scale superposition, thereby intensifying critical floating object characteristics; (2) an optimized CBAM attention mechanism to mitigate background noise interference and substantially elevate detection accuracy; (3) the incorporation of a minor target recognition layer to augment the model’s capacity to discern floating objects of differing dimensions across various environments; and (4) the implementation of the WIoU loss function to enhance the model’s convergence rate and regression accuracy. …”
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YOLOv8-DBW: An Improved YOLOv8-Based Algorithm for Maize Leaf Diseases and Pests Detection by Xiang Gan, Shukun Cao, Jin Wang, Yu Wang, Xu Hou

“…To solve the challenges of low detection accuracy of maize pests and diseases, complex detection models, and difficulty in deployment on mobile or embedded devices, an improved YOLOv8 algorithm was proposed. …”
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Multi-target personnel tracking algorithm for coal mine based on improved YOLOv7 and ByteTrack by Pengcheng QU, Jingzhao LI, Zechao LIU

“…Then, the CBAM attention mechanism was introduced into Neck to improve the feature perception ability of the model in complex scenes. …”
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A Model For Optimization of Knowledge Management Outsourcing Decision Using Genetic Algorithm by Ameneh Khadivar, Fatemeh Abbasi, Sheyda Akbarian

“…Purpose: The purpose of this study is to develop an optimization model for knowledge management outsourcing using a genetic algorithm. …”
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Short-Term Power Load Forecasting Using an Improved Model Integrating GCN and Transformer by Man Wu, Wanyi Feng, Xinya Li, Yunan Liu, Chuxin Cao

“…Improving the accuracy of power load forecasting is an important link in the optimization of power systems. …”
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A rapid detection method for egg quality using CARS and SSA⁃XGBoost improved by combining hyperspectral analysis by WANG Linyi, ZOU Qianying, SUN Qiang

“…Optimizing multiple hyperparameters of the XGBoost model through the Tartary Sea Salp Swarm Algorithm to improve the predictive performance of the XGBoost model. …”
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Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO by Baydaa Abdul Kareem, Salah L. Zubaidi

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Explanation and Optimizing Multi‐Model Blending Algorithm Using Random Variables Theory by Yu Wang, Yong Cao, Yue Shen, Ruixia Zhao, Xiaoqing Zeng, Li Yao, Kan Dai

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Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms by Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga, Ana Gómez

“…ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. …”
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Biomechanical Modeling of Selected Methods of Load Carriage to Improve Military Capabilities of Troops by Mostafa Hajlotfalian, Alireza Redaei, Heydar Sadeghi

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Multiobjective Demand Double-Layer Energy Consumption Optimization Strategy for Microgrid Based on Improved HPSOFA by Bin Zhang, Jue Wang, Bo Li

“…In order to optimize the economy and environmental protection of microgrid, this paper establishes a demand response model based on comprehensive satisfaction, combines the advantages of the classical multiobjective particle swarm algorithm and multiobjective firefly algorithm, and proposes a hybrid particle swarm optimization and firefly algorithm (HPSOFA) to solve the joint economic and environmental dispatch problem of microgrid and improve the wind and light consumption capacity. …”
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Identifying influential spreaders based on improving communication transmission model and network structure by Shimeng Zhang, Zejun Sun, Guan Wang, Haifeng Hu, Feifei Wang, Xiaoyan Sun

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Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits. by Mohsen Yoosefzadeh-Najafabadi, Dan Tulpan, Milad Eskandari

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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…This operation also reduces the computational cost by decreasing the amount of required feature map channels, while maintaining the effectiveness of the feature representation. (3) he Minimum Point Distance Intersection over Union loss function is employed to optimize bounding box detection during model training. (4) to construct the overall network structure, the Layer-wise Adaptive Momentum Pruning algorithm is used for thinning.ResultsExperiments on the TinyPerson dataset demonstrate that IYFVMNet achieves a 46.3% precision, 30% recall, 29.3% mAP50, and 11.8% mAP50-95.DiscussionThe model exhibits higher performance in terms of accuracy and efficiency when compared to other benchmark models, which demonstrates the effectiveness of the improved algorithm (e.g., YOLO-SGF, Guo-Net, TRC-YOLO) in small-object detection and provides a reference for future research.…”
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UWB Base Station Deployment Optimization Method Considering NLOS Effects Based on Levy Flight-Improved Particle Swarm Optimizer by Shengliang Wang, Ming Gao, Ling’ai Li, Dong Lv, Yingqi Li

“…In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor positioning area as the fitness function, and proposes an improved particle swarm optimization algorithm based on the Levy flight strategy (LPSO) to solve the optimization problem. …”
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Improved Phase Diversity Wavefront Sensing with a Deep Learning-Driven Hybrid Optimization Approach by Yangchen Wang, Ming Wen, Hongcai Ma

“…To address these challenges, this paper proposes a hybrid PDWS method that integrates deep learning with nonlinear optimization to improve efficiency and accuracy. The deep learning model provides an initial estimate of wavefront aberrations, which is further refined by the L-BFGS optimization algorithm to achieve high-precision reconstruction. …”
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Precise motion control for a space mining robot based on improved African vultures optimization by Baiyi Wang, Xinhua Liu, Marek Rydel, Dezheng Hua, Rafal Stanislawski, Hui Wang, Ke Feng, Zhixiong Li

“…Then, the optimal PID motion controller is developed based on the improved African vultures optimization algorithm (IAVOA). …”
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Anterior Cruciate Ligament Tear Detection Based on Combination of Convolutional Neural Network Enhanced by Improved Human Evolutionary Algorithm by Haibo Shen

“…This study proposes a new efficient technique for detecting tears of ACL based on the integration of a Convolutional Neural Network (CNN) and an improved version of Human Evolutionary Algorithm (IHEA). …”
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Coevolutionary Algorithm with Bayes Theorem for Constrained Multiobjective Optimization by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…By dynamically adjusting the selection of the auxiliary population based on prior knowledge, the algorithm significantly improves its adaptability to various CMOPs. …”
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An improved preconditioned conjugate gradient method for unconstrained optimization problem with application in Robot arm control by Lawal Muhammad, Mohammad Y. Waziri, Ibrahim Mohammed Sulaiman, Issam A.R. Moghrabi, Aceng Sambas

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