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481
Random Forest-Based Retrieval of XCO<sub>2</sub> Concentration from Satellite-Borne Shortwave Infrared Hyperspectral
Published 2025-02-01“…This paper proposes a method to predict the concentration of column-averaged CO<sub>2</sub> (XCO<sub>2</sub>) from shortwave infrared hyperspectral satellite data, using machine learning to avoid the iterative computations of the physical method. The training dataset is constructed using the Orbiting Carbon Observatory-2 (OCO-2) spectral data, XCO<sub>2</sub> retrievals from OCO-2, surface albedo data, and aerosol optical depth (AOD) measurements for 2019. …”
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482
Optimizing additive manufacturing workflows using model-based systems engineering
Published 2025-09-01“…Future iterations of ASAM will incorporate advanced algorithms for real-time parameter optimization and predictive analytics. …”
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483
3D Point Cloud Fusion Method Based on EMD Auto-Evolution and Local Parametric Network
Published 2024-11-01“…In the first stage, EMD is introduced as a key metric for evaluating the fusion results, and a point cloud fusion method based on EMD auto-evolution is constructed. The method uses an alternating iterative technique to sequentially update the variables and produce an initial fusion result. …”
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484
Optimal Allocation of Gas Supply Reliability in Natural Gas Pipeline System Based on Exterior Penalty Function Method
Published 2025-04-01“…Optimal allocation of gas supply reliability is an important part of gas supply reliability of natural gas pipeline system.In order to study the optimal allocation scheme of gas supply reliability with the lowest cost,a cost function model based on the gas supply capacity of the pipeline system was constructed.To address the limitation of traditional intelligent optimization algorithms (e.g.…”
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485
AI-Based Linguistic Frameworks for Monitoring Physical Health, Sports Performance, and Educational Contexts
Published 2025-01-01“…Rather, their perceptual feedback loops and adaptive interpretations are integrated into the iterative refinement of monitoring algorithms. The paper concludes by identifying emerging linguistic bottlenecks, reflecting on the application of AI-driven linguistic inference in the field of education and sports physiology, and proposing suggestions for scalable framework deployment. …”
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486
Research on Maneuvering Motion Prediction for Intelligent Ships Based on LSTM-Multi-Head Attention Model
Published 2025-03-01“…The results demonstrate that our proposed model significantly improves the accuracy of ship maneuvering predictions compared to standalone LSTM and MHAM algorithms and exhibits superior generalization performance.…”
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487
SG-ResNet: Spatially Adaptive Gabor Residual Networks with Density-Peak Guidance for Joint Image Steganalysis and Payload Location
Published 2025-04-01“…The reconstruction subnet synchronously constructs multi-scale features, preserves steganographic spatial fingerprints with channel-separated residual spatial rich model and pixel reorganization operators, and achieves sub-pixel-level steganographic localization via iterative optimization mechanism of feedback residual modules. …”
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488
Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows
Published 2025-03-01“…Abstract Full waveform inversion (FWI) is able to construct high‐resolution subsurface models by iteratively minimizing discrepancies between observed and simulated seismic data. …”
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489
MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation
Published 2025-01-01“…However, the existing sea ice segmentation algorithms for SAR images often fail to consider long-range contextual dependencies when capturing multiscale features, resulting in an inability to fully exploit multiscale global contextual information. …”
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490
Enhanced 3-D Reconstruction Method for Polarimetric Coherent Optimal-Based Tomographic SAR
Published 2025-01-01“…However, in the practical application, there are relatively few models and algorithms for full-polarized SAR joint 3-D imaging. …”
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491
Question-matching approach based on gradual machine learning
Published 2025-01-01“…Beginning with initially labeled instances, this approach gradually labels target instances in order of increasing hardness via iterative factor inference on a factor graph. The proposed solution first extracts diverse semantic features from different perspectives and then constructs a factor graph by fusing the extracted features to facilitate gradual learning from easy to hard. …”
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