Training dataset of "Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning"

Name: Training dataset of "Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning"
Creator: Jue Wang
License: https://creativecommons.org/licenses/by/4.0/
Keywords: Machine Learning

Citation Author(s):: Jue
Wang
Purdue University
Submitted by:: Jue Wang
Last updated:: Tue, 05/17/2022 - 22:18
DOI:: 10.21227/j49f-xh11
Data Format:: Excel
Research Article Link:: Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning
License:: Creative Commons Attribution

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Categories:: Machine Learning
Keywords:: soft robotics, Machine Learning, Multilayer perceptron (MLP)

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Abstract

This dataset is the supplementary material of an IEEE RAL paper named "Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning". It includes the z-displacement data derived from the FEA simulation, voltage input data derived from Matlab, and dataset for inverse application. The detailed description can be found in that paper.

Instructions:

The z-displacement data derived from the FEA simulation and voltage input data derived from Matlab are for training the regression model. The dataset for inverse application is the input of the regression model.

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I would like to analyze data

Submitted by Lakshmi Sri Tatiraju on Wed, 01/24/2024 - 12:08

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Dataset.zip (29.13 MB)

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Training dataset of "Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning"

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