Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

Model for Population Zero

Authors
Xiao Man Luo
Corresponding Author
Xiao Man Luo
Available Online May 2017.
DOI
10.2991/msmee-17.2017.197How to use a DOI?
Keywords
Population Zero,the multiple linear regression prediction
Abstract

New technologies, including personalized artificial augmentations units, will soon enable humans to inhabit manufactured cities on Mars by 2100. The first wave of migration, called Population Zero, will include 10,000 people.Population Zero aims to have optimal conditions in many workforce and social living factors.In this problem, we have different aspects to consider. First step, we defined some parameters that connect to those three prior elements to calculate. Next we set some norms to judge whether the system could meet the requirement. Secondly, to fetch data we generated a sample population of 10,000 people to emigrate to Mars. To make the simulation more appropriate, the distribution of citizen in terms of factors were taken into consideration.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
Series
Advances in Engineering Research
Publication Date
May 2017
ISBN
978-94-6252-346-3
ISSN
2352-5401
DOI
10.2991/msmee-17.2017.197How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiao Man Luo
PY  - 2017/05
DA  - 2017/05
TI  - Model for Population Zero
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 1014
EP  - 1017
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.197
DO  - 10.2991/msmee-17.2017.197
ID  - Luo2017/05
ER  -