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Dataset supporting the University of Southampton Doctoral Thesis : Design and Optimisation of an Uncrewed Aerial System Service Framework.

Dataset supporting the University of Southampton Doctoral Thesis : Design and Optimisation of an Uncrewed Aerial System Service Framework.
Dataset supporting the University of Southampton Doctoral Thesis : Design and Optimisation of an Uncrewed Aerial System Service Framework.
The data used to drive the simulation tool designed in the thesis "Design and Optimisation of an Uncrewed Aerial System Service Framework" by Robert Entwistle. This data set is the input variables that drive the simulation model. This needs to be used in conjuction with the AnyLogic model derived through this thesis. This dataset contains: 1 x database set (excel)
University of Southampton
Entwistle, Robert William
f90efac3-0017-4ee8-a078-dee48489795d
Entwistle, Robert William
f90efac3-0017-4ee8-a078-dee48489795d

Entwistle, Robert William (2023) Dataset supporting the University of Southampton Doctoral Thesis : Design and Optimisation of an Uncrewed Aerial System Service Framework. University of Southampton doi:10.5258/SOTON/D2575 [Dataset]

Record type: Dataset

Abstract

The data used to drive the simulation tool designed in the thesis "Design and Optimisation of an Uncrewed Aerial System Service Framework" by Robert Entwistle. This data set is the input variables that drive the simulation model. This needs to be used in conjuction with the AnyLogic model derived through this thesis. This dataset contains: 1 x database set (excel)

Text
dataset_readme.txt - Text
Download (753B)
Spreadsheet
DOUASSF_DB.xlsx - Dataset
Available under License Creative Commons Attribution.
Download (66kB)

More information

Published date: 24 May 2023

Identifiers

Local EPrints ID: 477053
URI: http://eprints.soton.ac.uk/id/eprint/477053
PURE UUID: f688d14a-57e1-41e5-a043-2eb836374c8f
ORCID for Robert William Entwistle: ORCID iD orcid.org/0000-0002-1453-2820

Catalogue record

Date deposited: 24 May 2023 17:08
Last modified: 31 Mar 2024 04:01

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