Intelligent deep learning-based dual-task approach for robust power quality event classification by Lipsa Ray, Pampa Sinha, Siddhanta Pani, Anshuman Nayak, Kaushik Paul, Chitralekha Jena, Md. Minarul Islam, Taha Selim Ustun

“…These findings underscore the model’s efficacy in real-time PQ monitoring, contributing to improved reliability and stability in evolving power systems.…”
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A Multi-Strategy ALNS for the VRP with Flexible Time Windows and Delivery Locations by Xiaomei Zhang, Xinchen Dai, Ping Lou, Jianmin Hu

“…This VRP-CS is formally modeled as a bi-objective optimization problem, which is an NP-hard problem. …”
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Transmission scheme for collaborative‐RIS‐aided NOMA system with multiple channels by Heyi Li, Hong Wang, Peiqi Li, Peiyu Wang

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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…The findings demonstrate that the proposed IoT-enabled model efficiently balances classification tasks, reduces congestion during algorithm execution, and minimizes energy waste. …”
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Lithium-Ion Battery State of Health Estimation Based on Feature Reconstruction and Transformer-GRU Parallel Architecture by Bing Chen, Yongjun Zhang, Jinsong Wu, Hongyuan Yuan, Fang Guo

“…The results show that the RMSE of the state of health estimation by the proposed method is 0.0071, which is an improvement of 61.41% in the accuracy of its baseline model.…”
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Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…In terms of target detection, the YOLOv7 algorithm is used, which effectively improves the accuracy and recall rate of target detection by optimizing the loss function. …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…In response to the limitations of current infrared and visible light image fusion algorithms-namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters-this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. …”
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Pig behavior recognition and disease warning based on compressed sensing and long-short term memory network by Ren Wang, Mingdong Zhao

“…In order to solve the problems of low precision and poor stability in pig behavior recognition process due to the deficiency of environment and hardware conditions such as complex lighting conditions, close color of target and background, poor camera Angle and parameters, a compressed sensing recognition algorithm via long and short term memory network for optimized feature extraction is proposed in this paper. …”
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Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

“…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
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Combating electricity fraud: Employing hybrid learning and computer vision for sustainable energy management by Jui-Sheng Chou, Nader Anwar Charaf, Dani Nugraha Limantono, Hoang-Minh Nguyen

“…Additionally, the study explores hybrid and ensemble AI models that combine the best-performing algorithms to improve prediction accuracy. …”
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Multi-Vehicle Object Recognition Method Based on YOLOv7-W by Xin Liu, Jingbin Zhao, Zhi Zhang, Rongxing Wu, Xun Li

“…Analysis of the XUPEI-CAR experimental dataset reveals significant variations in features across different traffic flow densities. To improve the matching accuracy of prior frames, the k-means++ clustering algorithm is employed to optimize the prior frame parameters. …”
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NMPC-Based 3D Path Tracking of a Bioinspired Foot-Wing Amphibious Robot by Heqiang Cao, Hailong Wang, Zhiqiang Hu

“…To this end, a nonlinear model predictive control (NMPC) algorithm is employed to compute optimal control inputs, as it effectively addresses the challenges of strong nonlinearity, coupling effects, and multi-objective optimization. …”
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Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…The DE algorithm works by seeking the best solution in a complex parameter space through iterations and performance evaluations, thereby significantly enhancing the performance of the forecasting model. …”
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Research on planning and demand matching strategies for intelligent material supply chains under carbon constraints by Shao Xuwei, Wu Jianfeng, Ge Junping, Wang Jianguo, Hu Kairui, Qiu Yang, Ju Chunhua, Xu Jiaming

“…Therefore, starting from the matching fitness of both supply and demand sides, this paper constructs a dynamic matching decision framework that is more in line with the actual operation logic, and introduces a dynamic matching algorithm based on multi-factor stimulus value and response threshold to improve the adaptability and responsiveness of the model. …”
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Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…Decision tree (DT), gradient boosting tree (GBT), Naïve Bayes (NB), and random forest (RF) algorithms are used to determine the best model. The comparative analysis of ML algorithms revealed that the GBT algorithm exhibits superior predictive capabilities regarding HPPT bench failure predictions. …”
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Application of 5G + edge computing technology in intelligent monitoring construction of electricity business office by Wei Cui, Junwei Li, Wei Ge, Bo Zhang, Tianwei Liu

“…This paper also proposes an edge scheduling algorithm based on game theory, which enables each edge device to choose the optimal data processing task according to its own utility function through a non-cooperative game model, realizing the optimization of the efficacy and accuracy of data processing. …”
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The Use of General Inverse Problem Platform (GRIPP) as a Robust Backtracking Solution by Nikolas Gomes Silveira de Souza, Jader Lugon, Alexandre Macedo Fernandes, Ramiro Joaquim de Jesus Neves, Antônio José da Silva Neto

“…This study addresses the challenge of identifying pollutant sources in aquatic coastal environments using inverse problem techniques hampered by particularities in hydrodynamic and Lagrangian models. An approach is presented employing the General Inverse Problem Platform (GRIPP) coupled with a General Simulated Annealing (GenSA) algorithm for robust backtracking. …”
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Three-dimensional image-guided navigation technique for femoral artery puncture by Yunmeng Zhang, Shenglin Liu, Qiang Zhang, Qingmin Feng

“…An improved ICP method is implemented to optimize surface point cloud alignment, providing higher efficiency and accuracy compared to conventional approaches. …”
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Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction. by Kang Xu, Bin Pan, MingXin Zhang, Xuan Zhang, XiaoYu Hou, JingXian Yu, ZhiZhu Lu, Xiao Zeng, QingQing Jia

“…Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to accurately model the spatial relationships in complex road networks; and (3) end-to-end training, which often results in unclear optimization directions for model parameters, thereby limiting improvements in predictive performance. …”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
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