Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

“…On this model, the improved DINO model achieved a maximum AP of 81.8%, outperforming the YOLOv7 model by 5.6%, with an FPS of 24 frames per second. …”
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Predictive modeling of electrochromic performance in ammonium metatungstate solutions using machine learning algorithms by Bocheng Jiang, Honglong Ning, Muyun Li, Rihui Yao, Chenxiao Guo, Yucheng Huang, Zijie Guo, Dongxiang Luo, Dong Yuan, Junbiao Peng

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Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

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Prediction and reliability analysis of rigid pipeline response in soft soil using improved particle swarm neural network by Laifu Song, Shun Zhang, Jun Wang, Hongtao Fu, Jiayu Cai

“…The simulation results are validated against data from field tests. Second, an improved particle swarm optimization (PSO) algorithm is introduced to optimize the weights and thresholds of a backpropagation neural network (BPNN). …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…It also requires fewer parameters and takes minimum training time. • The major contribution of this study is the design of an optimized, efficient and enhanced deep learning technique for multiclass rice crop disease detection embracing with batch normalization, dropout and genetic optimization algorithm to improve generalization power and restrict the overlearning capability for seen and unseen data. • Proposed VCNet, a shallow model with deep feature extraction, employs VGG16 layers for initial extraction fused with custom CNN architecture to correctly detect the challenging classes of diseases like sheath rot in multiclass classification. • The most significant observation is that VCNet accurately predicts the rice disease for each class of diseases under study whereas the existing powerful models largely misclassified for some classes of diseases in multiclass classification.…”
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Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

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Research on the method of weight calculation and equipment arrangement optimization of tramcar by DUAN Huadong, LIU Xiaofeng, JIANG Zhongcheng, ZHANG Bo

“…Based on Isight optimization platform, multi-objective optimization algorithm was adopted to improve the equipment layout. …”
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Optimized Ensemble Model to Predict the Compatibility of Automobiles With Hybrid Electric Vehicles by Rohit Bajaj, Deepika Sharma, Ruchika Gupta, Shonak Bansal, Payal Patial, Krishna Prakash

“…Through rigorous testing and refinement, the proposed model exhibits improved accuracy, elevating performance from 81.76% to 86.68%. …”
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Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

“…To solve the resulting optimization problem efficiently, we develop a tailored algorithm based on operator splitting techniques, significantly improving computational efficiency without sacrificing accuracy. …”
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Leveraging prior mean models for faster Bayesian optimization of particle accelerators by Tobias Boltz, Jose L. Martinez, Connie Xu, Kathryn R. L. Baker, Zihan Zhu, Jenny Morgan, Ryan Roussel, Daniel Ratner, Brahim Mustapha, Auralee L. Edelen

“…Abstract Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. …”
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Optimizing additive manufacturing workflows using model-based systems engineering by Mohamed Amine Daoud, Khadija Bekkay Haouari, Meriem Hayani Mechkouri, Amine Ennawaoui, Hicham El hadraoui, Ilias Naser, Mustapha Ouardouz, Kamal Reklaoui

“…Future iterations of ASAM will incorporate advanced algorithms for real-time parameter optimization and predictive analytics. …”
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Research on cutting mechanism and process optimization method of gear skiving by Peng Wang, Yuanchao Ni, Xiaoqiang Wu, Jiaxue Ji, Geng Li, Jiahao Wu

“…Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…Next, the Haar Wavelet Downsampling module (HWD) is employed to expand the receptive field, reduce model complexity, and improve both training and inference speeds. …”
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Numerical modeling and neural network optimization for advanced solar panel efficiency by Udit Mamodiya, Indra Kishor, Mohammed Amin Almaiah, Monia Hamdi, Rami Shehab, Tayseer Alkhdour

“…Conventionally, such optimization techniques—MPPT (Maximum Power Point Tracking) along with heuristic algorithms—suffer significantly from slow adaptability and track sub optimality under dynamic environments. …”
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A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…Future research efforts should focus on enhancing data acquisition and analysis techniques, optimizing the model structure, and improving the model adaptability and accuracy across various application scenarios.…”
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Optimal ecological restoration strategy development based on value-cost trade-offs by Yunxuan Liu, Cui Zhang, Miaomiao Xie, Jingyi Xie

“…In addition, we searched for Pareto-optimal solutions using the nondominated sorting genetic algorithm II (NSGA-II) to balance the trade-offs between different objectives. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…The proposed method achieves a mean average precision (mAP) of 82.04% on KITTI, representing an improvement of 2.34% over the baseline model. For heavily occluded objects on CityPersons, the Log Average Miss Rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>MR</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>) is reduced to 40.31%, which is a decrease of 9.65% compared to the baseline. …”
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An Improved Correlation Filtering Method for Tracking Maritime Small Targets of GF-4 Staring Satellite Sequence Images by Deyang Zhang, Yao Xu, Haimin Hu

“…The multi-scale features of the target based on time and space information are extracted, and the target tracking is realized by improved kernel correlation filtering algorithm. By comprehensively utilizing unscented Kalman filter model and target significance features, tracking results are optimized to improve tracking accuracy. …”
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Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis by Zhi-guang Jiang, Xiao-tian Shi

“…The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. …”
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