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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GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

“…Our approach utilizes an improved GhostNetV3 to bolster feature extraction capabilities. …”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…[Methods]The YOLOv11-AP2S model enhanced the YOLOv11 algorithm by incorporating a series of improvements to its backbone network, neck, and head components. …”
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Fixed Depth Control Strategy for Remotely Operated Vehicle Based on Improved Model Predictive Control Algorithm by Shuo YANG, Honghui WANG, Xinyu LIU, Xin FANG, Guanghao LI, Guijie LIU

“…First, a nonlinear marine predator algorithm(NMPA) was introduced to optimize key control parameters of MPC, ensuring fast and precise depth tracking of ROVs in complex marine environments. …”
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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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Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…By balancing exploration-exploitation using CSA while adapting search parameters through reinforcement learning, RL-CSA ensures scalability, improved DG utilization (98%), and better voltage stability (< 0.005 p.u.), making it a robust and intelligent alternative for modern smart grid optimization.…”
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Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
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Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

“…This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). …”
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Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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Particle Swarm Optimization on Parallel Computers for Improving the Performance of a Gait Recognition System by Shahla A. Abdulqader, Hasmek A. Krekorian

“…In recent years, the gait recognition (GR) using particle swarm optimization (PSO) algorithm (OSO) has been execute very fast and accurate with single computer, but with the appearance of parallel computing (PC), it was necessary to use this technique to improve the results of GR. …”
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Edge detection of aerial images using artificial bee colony algorithm by Nurdan Akhan Baykan, Elif Deniz Yelmenoglu

“…In this paper, aerial images are used for edge information extraction by using Artificial Bee Colony (ABC) Optimization Algorithm. Procedures were performed on gray scale aerial images which are taken from RADIUS/DARPA-IU Fort Hood database. …”
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Advanced strategies for the efficient optimization and control of industrial compressed air systems by D. Salomone-González

“…Real-time data transmission, powered by big data algorithms, enables continuous analysis to optimize the overall performance of the compressor plant. …”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…This hybridization implements Particle Swarm Optimization and a neural network to improve results while slowing convergence and improving efficiency. …”
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Multi-objective: hybrid particle swarm optimization with firefly algorithm for feature selection with Leaky ReLU by Ashish Kumar Singh, Anoj Kumar

“…This study proposes a novel optimization algorithm, LR-GPSOFA, designed to improve feature selection by enhancing computational efficiency and classification accuracy. …”
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Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

“…Despite this trade-off, the algorithm’s ability to minimize fleet size while fully utilizing vehicle capacity makes it the optimal choice in scenarios where these factors are critical. …”
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Hybrid Deep Neural Network Optimization with Particle Swarm and Grey Wolf Algorithms for Sunburst Attack Detection by Mohammad Almseidin, Amjad Gawanmeh, Maen Alzubi, Jamil Al-Sawwa, Ashraf S. Mashaleh, Mouhammd Alkasassbeh

“…The PSO algorithm was used to optimize the learning rate and the number of hidden layers, while the GWO algorithm was used to optimize the neuron weight. …”
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Critical sliding surface location method for anisotropic slope based on anisotropic yield criterion and optimization algorithm by Zhenfu Zhang, Yongjun Zhang, Sijia Liu, Mingzhong Gao, Fei Liu, Jintao Wang

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Multi-Objective Optimization Design of Ship Propulsion Shafting Based on Response Surface Methodology and Genetic Algorithm by ZHANG Cong, SHU Bingnan, ZHANG Jiangtao, JIN Yong

“…In order to reduce the power loss of the transmission equipment, enhance the transmission efficiency of the propulsion shafting, and improve the vibration performance of the shafting, a multi-objective optimization design of a ship shafting experimental platform is performed based on the response surface model and genetic algorithm. …”
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ACIVY: An Enhanced IVY Optimization Algorithm with Adaptive Cross Strategies for Complex Engineering Design and UAV Navigation by Heming Jia, Mahmoud Abdel-salam, Gang Hu

“…While the original Ivy Optimization Algorithm (IVYA) demonstrates a competitive performance, it suffers from limited inter-individual information exchange, inadequate directional guidance for local optima escape, and abrupt exploration–exploitation transitions. …”
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