Integrating Artificial Intelligence and Computational Algorithms to Optimize the 15-Minute City Model by Marwa Abouhassan, Samah Elkhateeb, Raneem Anwar

“…Furthermore, it elaborates on how the integration of artificial intelligence (AI) and computational tools can be utilized in optimizing the 15-minute city model. We reveal how AI-driven algorithms, machine learning techniques, and advanced data analytics can enhance urban planning, improve accessibility, and foster social integration. …”
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ACM-YOLOv10: Research on Classroom Learning Behavior Recognition Algorithm Based on Improved YOLOv10 by Beichen Qin, Haoyan Hu, Shaowen Du

“…To effectively integrate the research on learning engagement with teaching practices and accurately assess and analyze students’ learning behavior participation in the classroom to improve teaching quality, this paper proposes an improved YOLOv10 algorithm model, ACM-YOLOv10, targeting the issues of insufficient detection precision, missed detection, false detection, and slow speed of traditional recognition algorithms in classroom behavior detection under multi-scale scenarios and occluded targets. …”
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Improved Energy Efficient Anytime Optimistic Algorithm for PEGASIS to Extend Network Lifetime in Homogeneous and Heterogeneous Networks by Tadele A. Abose, Venumadhav Tekulapally, Samuel T. Daka, Diriba C. Kejela, Alemayehu E. Duguma, Desalegn T. Degaga

“…The proposed IEE AO algorithm is compared with several existing models, including low energy adaptive clustering hierarchy (LEACH), stable election protocol (SEP), ant colony optimization (ANT), and anytime optimistic (AO) algorithms, under both MAX energy and sequential energy criteria. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. …”
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ENGINE FAULT DIAGNOSIS BASED ON DEEP BELIEF NETWORK IMPROVED BY ADAPTIVE CROW SEARCH ALGORITHM (MT) by WANG Liang, TANG MingWei

“…In view of the fact that the selection of deep belief network（DBN） model parameters has great influence on the engine fault diagnosis results, ACSA is used to optimize the selection of its model parameters, and an engine fault diagnosis method based on DBN improved by ACSA is proposed. …”
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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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Elevator fault precursor prediction based on improved LSTM-AE algorithm and TSO-VMD denoising technique. by Hao Cao, Xiaoyan Du

“…This study proposes an advanced elevator fault precursor prediction method integrating Variational Mode Decomposition (VMD), Bidirectional Long Short-Term Memory (BILSTM), and an Autoencoder with an Attention Mechanism (AEAM), collectively referred to as the VMD-BILSTM-AEAM algorithm. This model addresses the challenges of feature redundancy and noise interference in elevator operation data, improving the stability and accuracy of fault predictions. …”
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A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning by Junyao Ding, Jianchao Du, Hejie Wang, Song Xiao

“…Then, the improved genetic algorithm is used to search for the global optimal feature subset further. …”
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GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

“…These factors contribute to the reduced accuracy and robustness of visual detection technologies based on segmentation algorithms within tobacco intelligent production systems, highlighting the need for a targeted segmentation model. …”
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Improved YOLOv8 Algorithm was Used to Segment Cucumber Seedlings Under Complex Artificial Light Conditions by Duokuo Zhang, Na Li, Mingfu Zhao, Kun Xu

“…Aiming at the challenging problem of cucumber seedling leaf segmentation under a complex artificial lighting environment, this study proposes an improved complex lighting YOLOv8 (CL-YOLOv8) model based on YOLOv8. …”
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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 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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