Wide & deep learning for predicting relative mineral compositions of sediment cores solely based on XRF scans, a case study from Pleistocene Paleolake Olduvai, Tanzania

This study develops a method to use deep learning models to predict the mineral assemblages and their relative abundances in paleolake cores using high-resolution XRF core scan elemental data and X-ray diffraction (XRD) mineralogical results from the same core taken at coarser resolution.It uses the XRF core scan data along with published mineralog

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Application of Federal Kalman Filter with Neural Networks in the Velocity and Attitude Matching of Transfer Alignment

The centralized Kalman filter is always applied in the velocity and attitude matching of Transfer Alignment (TA).But the centralized Kalman has many disadvantages, such as large amount of calculation, poor real-time performance, Sundials and low reliability.In the paper, the federal Kalman filter (FKF) based on neural networks is used in the veloci

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