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163 results on '"Yu, Tianbo"'

5. A Hybrid Deep Learning Model for Predictive Flood Warning and Situation Awareness using Channel Network Sensors Data

Author

Dong, Shangjia, Yu, Tianbo, Farahmand, Hamed, and Mostafavi, Ali

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The objective of this study is to create and test a hybrid deep learning model, FastGRNN-FCN (Fast, Accurate, Stable and Tiny Gated Recurrent Neural Network-Fully Convolutional Network), for urban flood prediction and situation awareness using channel network sensors data. The study used Harris County, Texas as the testbed, and obtained channel sensor data from three historical flood events (e.g., 2016 Tax Day Flood, 2016 Memorial Day flood, and 2017 Hurricane Harvey Flood) for training and validating the hybrid deep learning model. The flood data are divided into a multivariate time series and used as the model input. Each input comprises nine variables, including information of the studied channel sensor and its predecessor and successor sensors in the channel network. Precision-recall curve and F-measure are used to identify the optimal set of model parameters. The optimal model with a weight of 1 and a critical threshold of 0.59 are obtained through one hundred iterations based on examining different weights and thresholds. The test accuracy and F-measure eventually reach 97.8% and 0.792, respectively. The model is then tested in predicting the 2019 Imelda flood in Houston and the results show an excellent match with the empirical flood. The results show that the model enables accurate prediction of the spatial-temporal flood propagation and recession and provides emergency response officials with a predictive flood warning tool for prioritizing the flood response and resource allocation strategies.

Published
2020

43. Recovery of small orientation gradients in a recrystallized grain observed in 3D during ex-situ annealing

Author

Hong, Chuanshi, Zhang, Yubin, Yu, Tianbo, Liu, Wenjun, and Jensen, Dorte Juul

Abstract

We report the observation of a small orientation gradient (~0.5° over a few micrometers) in a recrystallized grain formed at the sample surface in pure Al and the elimination of this orientation gradient during subsequential ex-situ annealing. The observation is in 3D and done using synchrotron white-beam differential-aperture X-ray microscopy with high angular resolution of 0.01°. The elimination of the orientation gradient during subsequent annealing are analyzed and discussed.

Published
2022

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