PMD-Transformer: A Domain Generalization Approach for Person Re-Identification by Xingguo Jiang, Ling Yu, Guojun Lin, Yuchao Zhang

“…Finally, a new feedforward network (DRFNN) is used to enhance the mastery of spatial information and further improve the generalization performance of the model. …”
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The role of physical metallurgical relationships in enhancing alloy properties prediction and design: A case study on Q&P steel by Yong Li, Hua Li, Chenchong Wang, Pedro Eduardo Jose Rivera‐Diaz‐del‐Castillo

“…To address this, this study proposes a novel framework that combines PM knowledge graphs (PMKGs) with graph neural networks (GNNs) to predict the tensile properties of quenching and partitioning steels, using genetic algorithms for dual‐objective optimization. Compared to traditional artificial intelligence (AI) models, this framework shows significant advantages in predicting ultimate tensile strength (UTS) and total elongation (TEL) with higher accuracy and stability. …”
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Multiple UAV Swarms Collaborative Firefighting Strategy Considering Forest Fire Spread and Resource Constraints by Pei Zhu, Rui Song, Jiangao Zhang, Ziheng Xu, Yaqi Gou, Zhi Sun, Quan Shao

“…The multiple UAV swarm adaptive information-driven collaborative search (MUSAIDCS) algorithm and the resource-limited firefighting model were established. …”
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Vehicle-to-Vehicle Communication Channel Estimator Based on Gate Recurrent Unit by Jun-Han Wang, He He, Kosuke Tamura, Shun Kojima, Jaesang Cha, Chang-Jun Ahn

“…To alleviate such issues, this study proposes a channel estimation method by combining the sparrow search algorithm (SSA) and gated recurrent unit (GRU). In addition, this paper adds the attention mechanism to GRU to improve the robustness of the model. …”
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Characterization of immune microenvironment associated with medulloblastoma metastasis based on explainable machine learning by Fengmao Zhao, Xiangjun Liu, Jingang Gui, Hailang Sun, Nan Zhang, Yun Peng, Ming Ge, Wei Wang

“…Eight algorithms were evaluated, and the optimal model was selected. …”
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Development of a Novel Biomechanical Framework for Quantifying Dynamic Risks in Motor Behaviors During Aircraft Maintenance by Mingjiu Yu, Di Zhao, Yu Zhang, Jing Chen, Gongbing Shan, Ying Cao, Jun Ye

“…The model evaluates dynamic human postures and employs an inverse trigonometric function algorithm to quantify the loading effects on working joints. …”
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TDMA-based user scheduling policies for federated learning by Meixia TAO, Dong WANG, Rui SUN, Naifu ZHANG

“…To improve the communication efficiency in FL (federated learning), for the scenario with heterogeneous edge user's computing capacity and channel state, a class of time division multiple access (TDMA) based user scheduling policies were proposed for FL.The proposed policies aim to minimize the system delay in each round of model training subject to a given sample size constraint required for computing in each round.In addition, the convergence rate of the proposed scheduling algorithms was analyzed from a theoretical perspective to study the tradeoff between the convergence performance and the total system delay.The selection of the optimal batch size was further analyzed.Simulation results show that the convergence rate of the proposed algorithm is at least 30% higher than all the considered benchmarks.…”
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Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach. by Josh L Espinoza, Chris L Dupont, Aubrie O'Rourke, Sinem Beyhan, Pavel Morales, Amy Spoering, Kirsten J Meyer, Agnes P Chan, Yongwook Choi, William C Nierman, Kim Lewis, Karen E Nelson

“…Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. …”
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Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations by Min-Hwa Choi, Woongchang Yoon

“…The XGBoost Regressor (XGBR) is optimized using genetic-algorithm-based hyperparameter tuning, reducing mean squared error (RMSE) from 20.9531 to 19.6387, mean absolute error (MAE) from 13.6821 to 12.6753, and improving coefficient of determination (R2) from 0.2791 to 0.2949. …”
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Combined CNN-BiLSTM-Att tourism flow prediction based on VMD-MWPE decomposition reconstruction by Maomao Luo, Danhong Chen, Xinxing Hou, Kang Luo, Tao Wang

“…Finally, the CNN-BiLSTM prediction model, incorporating an attention mechanism and optimized using a genetic algorithm, was applied to generate the final prediction results. …”
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Integrating Machine Learning and Material Feeding Systems for Competitive Advantage in Manufacturing by Müge Sinem Çağlayan, Aslı Aksoy

“…Material feeding systems are of pivotal importance in the optimization of productivity, with attendant improvements in quality, reduction of costs, and minimization of delivery times. …”
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Short-term forecast of wind power based on the division of wind speed fluctuation characteristics by QIAO Titang, XIE Lirong, YE Jiahao, GAO Yang, DAI Bing

“…The dynamic time warping algorithm is used to mine the fluctuating wind similar data in the historical data, and a training sample data set is constructed combining with the corresponding historical wind power; a hunger game search algorithm is used to optimize the hyperparameters of the gated recurrent unit neural network, and a combined prediction model for three fluctuation stages is established. …”
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Fuzzy incidence coloring under structural operations for communication channel allocation by Angmo Deji, Qian Wang, Li Zhou

“…By applying FICN, the minimum number of frequency signals required to avoid communication interference can be determined, thereby enabling optimized channel allocation, reduced interference, and improved communication management under constrained resources.…”
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Proposing Smart System for Detecting and Monitoring Vehicle Using Multiobject Multicamera Tracking by Phat Nguyen Huu, Bang Nguyen Anh, Quang Tran Minh

“…To achieve this, we use the YOLO model for detection in conjunction with the DeepSORT algorithm for precise vehicle tracking on each camera. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…The proposed G-RCenterNet algorithm is embedded into a robotic grasping system, where a structured light depth camera captures target images, and the grasp detection network predicts the optimal grasp box. …”
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Tactical intent-driven autonomous air combat behavior generation method by Xingyu Wang, Zhen Yang, Shiyuan Chai, Jichuan Huang, Yupeng He, Deyun Zhou

“…Built around this, the decision-making process of pilot behavior is analyzed, and a reward mapping model from intent to behavior is established. Finally, to address the problems of poor stability and slow convergence speed of deep reinforcement learning algorithms in large-scale state-action spaces, the dueling-noisy-multi-step DQN algorithm is devised, which not only improves the accuracy of value function approximation but also enhances the efficiency of space exploration and network generalization. …”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…The core of this method is an improved algorithm based on the TD3, which is enhanced by the incorporation of the CQL algorithm to improve the stability of the collaborative control strategy. …”
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Deep Reinforcement Learning-Based Impact Angle-Constrained Adaptive Guidance Law by Zhe Hu, Wenjun Yi, Liang Xiao

“…We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…Logistic Regression and Multilayer Perceptron also showed robust results, but SGD was superior in most metrics. For the Rules classifiers, JRip outperformed others due to its iterative rule optimization, whereas OneR's simplicity resulted in the lowest performance. …”
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Pilot design for underwater MIMO cosparse channel estimation based on compressed sensing by Yun Li, Lingxia Liao, Shanlin Sun, Zhicheng Tan, Xing Yao

“…In multiple-input multiple-output–orthogonal frequency-division multiplexing underwater acoustic communication systems, the correlation of the sampling matrix is the key of the channel estimation algorithm based on compressed sensing. To reduce the cross-correlation of the sampling matrix and improve the channel estimation performance, a pilot design algorithm for co-sparse channel estimation based on compressed sensing is proposed in this article. …”
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