Datasets

subject: Machine Learning type: dataset

Total is 18 Results
Data for Characterization of Acoustic Emissions from Analogue Rocks using Sparse Regression-DMDc

10.4231/4K64-4818

Charles Fieseler , Chven Mitchell , Laura J Pyrak-Nolte ORCID logo , Nathan Kutz

06/14/2022

Acoustic waveforms collected during the monitoring of moisture loss in synthetic rock samples composed of mortar, and mortar with either distributed clay or localized clay, under ambient laboratory conditions.

acoustic signals clay cracking Fractures Machine Learning Physics

Genome-wide, Organ-delimited gene regulatory networks (OD-GRN) provide high accuracy in candidate Transcription Factor (TF) selection across diverse processes

10.4231/50R5-EM83

Karen Hudson , Kranthi K Varala ORCID logo , Ying Li

01/04/2024

Organ-specific gene expression datasets that include hundreds to thousands of experiments allow reconstruction of gene regulatory networks and discovery of transcriptional regulators various pathways and processes.

Arabidopsis thaliana Gene regulatory networks k-nearest neighbor (kNN) linear support vector machines (SVM) Machine Learning Systems biology

Modeling the Sea Level Changes in Guam

10.4231/0A0F-7A84

Avnika Manaktala ORCID logo

10/14/2019

This project works on understanding the different statistical models that are available to analyze and predict mean sea level changes in Guam.

Climate Change Data Education Earth and Atmospheric Sciences FAIR Data Machine Learning Sea level rise Statistical analysis Statistical Methods

Structural attributes derived from Google Street View imagery, Louisiana coastal zone

10.4231/1TZX-BR43

David R Johnson ORCID logo , Ed Delp ORCID logo , Fu-Chen Chen ORCID logo , 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

Evaluating Economic Opportunities for Product Recycling via the Sherwood Principle and Machine Learning - Supporting Information

10.4231/E80W-7941

Aihua Huang , John W. Sutherland ORCID logo , Sidi Deng ORCID logo , Xiaoyu Zhou , Yuehwern Yih ORCID logo

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

Data of global wetland methane emissions from artificial neural network modeling v1.0

10.4231/3YX4-EY30

Licheng Liu ORCID logo , Qianlai Zhuang ORCID logo

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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