Elastic regularization networks for enhanced UAV visual tracking by Qingjiao Meng, Ji Li, Yan Jin, Zhaotian Deng

“…However, most DCF-based trackers rely on predefined regularization terms and update their appearance models frame-by-frame, leading to increased computational complexity. …”
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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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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…In treatment planning, AI could improve approaches by optimizing surgical resection, radiotherapy regimen, and chemotherapy protocols. …”
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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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Factors influencing the effectiveness of SM-VCE method in solving 3D surface deformation by Xupeng Liu, Guangyu Xu, Mingkai Chen, Tengxu Zhang

“…The latter type applies to earthquakes that do not cause surface ruptures and have extensive blind faults. Currently, most research focuses on improving the above types of methods. …”
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User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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Research on Dynamic Storage Location Assignment of Picker-to-Parts Picking Systems under Traversing Routing Method by Xiangbin Xu, Chenhao Ren

“…Then, the adjustment gain model of dynamic storage location assignment is built, and a genetic algorithm is designed to find the final adjustment solution. …”
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Robust Planning for Hydrogen-Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage by Shufan Wang, Dong Yang, Linglu Zhang, Lingzhi Chenmei

“…This paper proposes an optimal planning model for the hydrogen-based integrated energy system (HIES) considering power to heat and hydrogen (P2HH) and seasonal hydrogen storage (SHS) to take full advantage of multienergy complementarity. …”
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Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning by Xiaojie Li, Chunliang Jiang, Qingyan Xie, Huiquan Wang, Jiameng Xu, Guanjun Liu, Panpan Chang, Guang Zhang

“…The soft-voting ensemble algorithm achieved an optimal predictive performance with an AUC of 0.839 (95% CI 0.786–0.889) for the all-features model, while logistic regression using common features achieved an AUC of 0.767 (95% CI 0.704–0.825), outperforming ROX and mROX indices. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

“…Also, the most applied machine learning algorithms are Linear Regression (LR), Random Forest (RF), and Gradient Boosting Trees (GBT) whereas the most applied deep learning algorithms are Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM). …”
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Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
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Hyperspectral Detection of Pesticide Residues in Black Vegetable Based on Multi-Classifier Entropy Weight Method by Rongchang Jiang, Guoqiang Zhuang, Shijie Xie, Yang Wang, Guoqi Zhang, Dandan Qu, Wanzhi Wen

“…The entropy weight method was then used to optimize model weights, developing the multi-classifier entropy weighted method algorithm to improve detection accuracy and robustness. …”
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