The energy reconstruction algorithm for high injection background by Kuzmin Alexander, Miyabayashi Kenkichi

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Multi-Objective Robust Optimization Reconstruction Algorithm for Electrical Capacitance Tomography by Xuejie Yang, Jing Lei, Qibin Liu

“…Qualitative and quantitative evaluation results demonstrate that the proposed method surpasses mainstream imaging algorithms, enhancing the automation level of the reconstruction process and image quality while exhibiting exceptional robustness. …”
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A Multi-Frequency Iterative Method for Reconstruction of Rough Surfaces Separating Two Penetrable Media by Ahmet Sefer, Ali Yapar, Hakan Bagci

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Analysis method combining improved AE algorithm and signal reconstruction in mechanical faults by Zhenhua Niu

“…Traditional diagnostic methods have shortcomings in accuracy and robustness.MethodsTherefore, the study integrates variational autoencoders with long short-term memory network models, enhances them using dropout methods, and proposes a hybrid diagnostic analysis model that combines improved autoencoder algorithms and signal reconstruction.ResultsThe experiment outcomes indicated that under the slow degradation mode of the bearing, the precision, recall, F1 score, and overall accuracy of the improved autoencoder model were 0.931, 0.933, 0.920, and 0.939, respectively, which were better than the pre-modified model. …”
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Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

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Sem-SLAM: Semantic-Integrated SLAM Approach for 3D Reconstruction by Shuqi Liu, Yufeng Zhuang, Chenxu Zhang, Qifei Li, Jiayu Hou

“…Meanwhile, to deeply excavate the semantic information in images, a pre-trained frozen 2D segmentation algorithm is employed to extract semantic features, providing a powerful support for 3D environmental reconstruction. …”
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Image reconstruction method based on backprojection filtration algorithm in C-arm computed tomography by Xianchao Wang, Qilin Wu, Pan Xu, Zheng Lu

“…In addition, unlike the original BPF algorithm, the scanning angle integration interval in the backprojection of the proposed method is fixed, which improves the reconstruction efficiency and parallelism. …”
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Unsupervised feature selection algorithm based on L 2,p-norm feature reconstruction. by Wei Liu, Qian Ning, Guangwei Liu, Haonan Wang, Yixin Zhu, Miao Zhong

“…In this paper, we propose an unsupervised feature selection method named unsupervised feature selection algorithm based on [Formula: see text]-norm feature reconstruction (NFRFS). …”
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Robust Adaptive Beamforming Algorithm for Sparse Array Based on Covariance Matrix Reconstruction Technology by Yuxi Du, Weijia Cui, Yinsheng Wang, Chunxiao Jian, Jian Zhang

“…To solve this problem, we propose two algorithms that are suitable for a variety of SA. In the first method, assuming that the desired signal is a non-Gaussian signal, the desired signal direction vector (DSDV) is estimated using the fourth-order cumulant, and then the interference plus noise covariance matrix (INCM) is reconstructed by integrating the area outside the desired signal. …”
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From Historical Archives to Algorithms: Reconstructing Biodiversity Patterns in 19th Century Bavaria by Malte Rehbein

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An Algorithm to Develop a Satellite‐Based Atmospheric River Database by Tianying Liu, Shineng Hu

“…In this study, we propose an algorithm to reconstruct the observed vertically integrated vapor transport (IVT) field using two satellite‐observed quantities, vertically integrated water vapor and sea surface winds. …”
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Method for reconstructing safety and arming motion process by integrating Kalman filter and KCF by Yinhuan Zhang, Qinkun Xiao, Xing Liu, Yongquan Wei, Jingyun Xue

“…Abstract This paper addresses the challenge of reconstructing the motion process of the safety and arming (S&A) mechanism in fuze by transforming the problem into a target detection and tracking problem. …”
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Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm by Lutai Wang, Zhen Liu, Xingyu Gu, Danyu Wang

“…This paper proposes a three-dimensional (3D) reconstruction method for GPR images, integrating the back-projection (BP) imaging algorithm to accurately determine the size, location, and other parameters of road structural defects. …”
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A Geometric Semantic Enhanced TomoSAR Reconstruction Algorithm in an Urban Area: Analysis and Application by Chunyi Wang, Qiancheng Yan, Xiaolan Qiu, Yitong Luo, Lingxiao Peng, Zhe Zhang

“…In this paper, we propose a Geometric Semantic Enhanced TomoSAR Reconstruction Algorithm (Geo-SETRA) for urban area. Geo-SETRA integrates geometric structures, extracted from TomoSAR point clouds, as prior distributions for elevation estimation using Bayesian methods. …”
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A Deformation Reconstruction Strategy for Integrated Truss Structures Subjected to Thermal–Mechanical Load by Zexing Yu, Xiaofei Ma, Jialong Zhu, Dayu Zhang, Yonggang Xue, Pengfei Huang, Yichen Li, Hao Li

“…The proposed approach utilizes Ko displacement theory as the core algorithm, while the least squares optimization method is employed to determine the integration with unknown initial values during the reconstruction process. …”
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Underwater Target 3D Reconstruction via Integrated Laser Triangulation and Multispectral Photometric Stereo by Yang Yang, Yimei Liu, Eric Rigall, Yifan Yin, Shu Zhang, Junyu Dong

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Adaptive filter parameter reconstruction technology for rocket inertial navigation/satellite integrated navigation system by Zhijie Yang, Guoguang Chen, Mingli Niu, Xiaolong Yan, Xiaoli Tian, Guocui Zhang

“…A variety of enhanced algorithms based on Kalman filtering are currently employed as integrated filtering methods, which comprehensively address deviations in the system model to improve navigation performance. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Trapezoidal back projection for positron emission tomography reconstruction by Dóra Varnyú, Krisztián Paczári, László Szirmay-Kalos

“…Abstract Background In the back projection step of the 3D PET reconstruction, all Lines of Responses (LORs) that go through a given voxel need to be identified and included in an integral. …”
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Spatiotemporal analysis of ocean primary productivity in Bohai Sea estimated using improved DINEOF reconstructed MODIS data by Shuhan Jia, Linlin Bei, Yu Li, Quanhua Zhao

“…First, a new time-scale feature was defined for effectively preserving spatiotemporal characteristics during the reconstruction of missing remote sensing data. The proposed algorithm, which integrates MS-DINEOF for reconstructing sea surface temperature, chlorophyll-a concentration, photosynthetically active radiation, and diffuse attenuation coefficient at 490 nm data, with VGPM for OPP estimation, was implemented for the Bohai Sea from 2010 to 2021. …”
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