4D trajectory lightweight prediction algorithm based on knowledge distillation technique by Weizhen Tang, Jie Dai, Zhousheng Huang, Boyang Hao, Weizheng Xie

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Classification of LPG Gas Usage Satisfaction Level Using The Naïve Bayes Algorithm by Angelia Melani Adrian, Bella Alisia Patras, Junaidy B. Sanger

“…The model achieved an accuracy of 89.3% with a 70:30 training-to-test data split, 91.2% with an 80:20 split, and 94.0% with a 60:40 split, indicating that performance varied based on the proportion of training and test data used.…”
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Robust Recursive Algorithm under Uncertainties via Worst-Case SINR Maximization by Xin Song, Feng Wang, Jinkuan Wang, Jingguo Ren

“…The performance of traditional constrained-LMS (CLMS) algorithm is known to degrade seriously in the presence of small training data size and mismatches between the assumed array response and the true array response. …”
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Multi-Task Perception Algorithm for Rail Transit Scenarios Based on Triplet Attention by GAO Rui, XIONG Yanping, WEI Chenfeng, XIE Guotao, GAO Ming

“…Moreover, by introducing differentiable parameters to optimize the data augmentation strategy, more diverse training samples were generated. Finally, a triplet attention mechanism was incorporated to address the original YOLOP algorithm's deficiency of losing key information during feature extraction. …”
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Source Type Recognition Algorithm of Radio Emission using Radial Basis Functions by V. F. Korotkov, R. S. Zyryanov

“…The algorithm is based on splitting training data classes into sub-classes, and using them for making a decision about the type of radio source. …”
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Pursuit-Interception Strategy in Differential Games Based on Q-Learning-Cover Algorithm by Yu Bai, Di Zhou, Zhen He

“…Through extensive model training, the successful capture of the evader by the pursuers in a three-on-one scenario was achieved. …”
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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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Implementation of Computer-Aided Piano Music Automatic Notation Algorithm in Psychological Detoxification by Xinmei Zhang

“…This paper analyzes the modeling of a computer-aided piano music automatic notation algorithm, combines the influence of music on psychological detachment, and designs the piano music automatic notation algorithm in psychological detachment model construction. …”
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Hybrid genetic algorithm and deep learning techniques for advanced side-channel attacks by Faisal Hameed, Hoda Alkhzaimi

“…A critical challenge in training effective neural network models lies in hyperparameter optimization. …”
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Deep Belief Network-Based Multifeature Fusion Music Classification Algorithm and Simulation by Tianzhuo Gong

“…In this paper, the multifeature fusion music classification algorithm and its simulation results are studied by deep confidence networks, the multifeature fusion music database is established and preprocessed, and then features are extracted. …”
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Unsustainable artificial intelligence and algorithmically facilitated emissions: The case for emissions-reduction-by-design by Jutta Haider, Malte Rödl, James White

“…It introduces the notion of algorithmically facilitated emissions to initiate a shift from a logic of ‘climate collapse by design’ to a logic of ‘emissions reduction by design’. …”
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Multi-Model Segmentation Algorithm for Rotator Cuff Injury Based on MRI Images by Mengqi Li, Jingchao Fang, Haonan Hou, Li Yuan, Jin Guo, Zhenlong Liu

“…A dataset of 376 patients with 5640 images was used for training, with an additional 94 patients and 1410 images reserved for testing. …”
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Scene Matching Method for Children’s Psychological Distress Based on Deep Learning Algorithm by Junli Su

“…The results show that the deep learning algorithm can have a deep and abstract mining on the characteristics of children’s psychological distress scenes and obtain a large amount of more representative characteristic information through training on large-scale data, thereby improving the accuracy of classification and matching of children’s psychological distress scenes. …”
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VF-CART: A communication-efficient vertical federated framework for the CART algorithm by Yang Xu, Xuexian Hu, Jianghong Wei, Hongjian Yang, Kejia Li

“…There is an increasing trend in adapting machine learning algorithms to the VFL setting. As a category of prevalent machine learning algorithms, decision tree and random forests in VFL have attracted widespread interest. …”
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Multimodal Fusion Image Stabilization Algorithm for Bio-Inspired Flapping-Wing Aircraft by Zhikai Wang, Sen Wang, Yiwen Hu, Yangfan Zhou, Na Li, Xiaofeng Zhang

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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…This method achieves fast detection while maintaining high accuracy, transforms the problem of target detection into a regression problem, and completes the location and classification of the target directly. In the training and deployment phase of the algorithm, the first-stage object detection algorithm uses pruning and quantization techniques to reduce the model size, which is suitable for running in mobile devices or embedded systems with limited resources. …”
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A new algorithm to assess the risk of malignancy in premenopausal patients with pelvic mass by M. S. Katsyuba, R. Sh. Khasanov, T. I. Madzhidov, G. Z. Muratova, G. A. Usmanova, A. F. Akhmetzyanova, A. Rakhimbekova, V. V. Terentyeva, G. R. Fakhrutdinova

“…Objective: to elaborate a new algorithm, based on serum CA125, HE4 and age, to assess the risk of malignancy in premenopausal patients with pelvic mass, which performs better than Risk of Ovarian Malignancy Algorithm (ROMA).Materials and methods. …”
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Application of optimized VMD in fault diagnosis of motor bearings of high-speed train by WANG Tao, SHI Yongjin, LI Jiwei, WANG Jinping

“…Aiming at the difficulty in extracting early faults of high-speed train motor bearings under the background of strong noise, an optimized VMD algorithm was proposed. …”
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Research on Cooperative Velocity Planning Technology for Urban Rail Train Virtual Coupling by HUANG Qiang, LI Cheng, YUAN Xiwen, CHEN Lin, LUO Jiaxiang

“…Based on the key requirements for urban rail trains, namely punctuality, comfort and sufficient time for platform operations, this study proposed a cooperative speed planning algorithm for virtual coupling, featuring information centralized decision-making, following an investigation into train traction and braking characteristics, vehicle kinematics and dynamics models. …”
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A Method of Velocity Curve Calculation for Train Based on Accurate Running Time by TIAN Changyu, LIU Jiazheng, ZHANG Chao

“…In order to improve the accuracy of train running time between stations in automatic train operation (ATO) mode, and also to make it be possible to adjust the plan based on interval time for automatic train supervision (ATS), it proposed a calculation scheme of recommended speed curve based on accurate running time. …”
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