Experimental Data Assimilation
Experimental Data Assimilation is a computational framework in inverse problems in mechanics that integrates experimental measurements with numerical models to optimally estimate system states or parameters by minimizing discrepancies between observed data and model predictions.
41
Publications
1.3K
Citations
177
Authors
86
Institutions
Publications per year
2017–2026
7
41
Zhiwei Jiang, Zhongxin Chen, Jin Chen et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2014 · 92 citations · Full text
Agriculture, Agronomy, Crop Sciences +16
Hajime Nakamura, Ko Koizumi, Nobutaka MANNOJI · Journal of the Meteorological Society of Japan Ser II · 2004 · 65 citations · Full text
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86
Meteorological Research Institute
Tsukuba, Japan
4 h-index
11 publications
246 citations
Japan Meteorological Agency
Tokyo, Japan
3 h-index
9 publications
307 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
13 publications
242 citations

Delft University of Technology
Delft, The Netherlands
2 h-index
2 publications
36 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
5 publications
231 citations
Planetary Science Institute
Tucson, United States
2 h-index
5 publications
215 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
2 h-index
3 publications
158 citations
University of California, Berkeley
Berkeley, United States
2 h-index
8 publications
164 citations
1–8 of 86
5 publications · 131 citations
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JGR · 4 publications · 151 citations
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4 publications · 134 citations
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2 publications · 60 citations
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2 publications · 34 citations
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