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Fusion model: Data fusion is adopted to reduce the redundant sensory data during data collection.
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Sacks, W. J., Schimel, D. S. & Monson, R. K. Coupling between carbon cycling and climate in a high-elevation subalpine forest: a model-data fusion analysis.
By quantifying model structure and data requirements this new approach to evaluating model-data fusion has advanced the understanding of canopy transpiration.
Developments in data acquisition and model-data fusion may open the way for cropping systems models to have greater impact in real-world policy or practice settings, making a meaningful contribution to future agricultural productivity and sustainability.
Based on the HiWATER-MUSOEXE data, this study evaluated the spatial representativeness and uncertainty of EC CO2 flux measurements for upscaling to the grid scale using a scheme that combines a footprint model and a model-data fusion method.
It requires thorough examination using modern observational tools and techniques for model-data fusion.
The values of this parameter are restored from the NPP measurements using technique known as model-data fusion [39].
The recent development of techniques for model-data fusion [34] opens up possibilities for transforming process-based models into semi-empirical, process-based models.
The values of this parameter are restored from the NPP measurements using technique known as model-data fusion [ 39].
The recent development of techniques for model-data fusion [ 34] opens up possibilities for transforming process-based models into semi-empirical, process-based models.
Under the complicated electromagnetism circumstance, the model of data fusion control and guidance of surface-to-air missile weapon systems is established.
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