subject: Machine Learning type: dataset date: 2020
10.4231/E80W-7941
Aihua Huang , John W. Sutherland , Sidi Deng , Xiaoyu Zhou , Yuehwern Yih
09/03/2020
This repository contains the supporting information for the manuscript regarding Sherwood principle and Machine learning. All critical underlying data files, along with a flow chart that describes the methodologies applied in the paper are enclosed.
Circular Economy Empirical Models Environmental and Ecological Engineering Machine Learning Sherwood Principle
10.4231/1TZX-BR43
David R Johnson , Ed Delp , Fu-Chen Chen , Mohammad Jahanshahi
07/28/2020
Structural attributes relevant to flood risk (foundation height/type, square footage, number of stories, building type), produced using machine learning for automated image analysis of GSV images.
flood risk Industrial Engineering Machine Learning structure attributes
10.4231/3YX4-EY30
01/21/2020
Source code of an ANN model, site level data, input data, output data and visualization results, which are presented in the manuscript "Inventorying Global Wetland Methane Emissions Based on In Situ Data and an Artificial Neural Network...
Artificial Neural Network (ANN) Atmospheric Chemistry Modeling Biogeochemistry Earth and Atmospheric Sciences Interactive Data Language (IDL) Machine Learning Matlab Methane Dynamics Model (MDM) Methane Emission
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