Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

A Measurement Model to Determine the Ability of a Region to Provide Clean Water

Authors
Jing Tian
Corresponding Author
Jing Tian
Available Online June 2016.
DOI
10.2991/mecs-17.2017.24How to use a DOI?
Keywords
multivariable linear regression, Grey Prediction, DGM(2,1)
Abstract

Freshwater resources are the basis for the survival of many organisms, especially for human. However, freshwater resources are gradually scarce. To provide people with more freshwater, the first thing we need to do is to determine the ability of a region to provide clean water to meet the needs of its population. In this paper, in order to determine the ability of a region to provide clean water to meet the needs of its population, we will build the measurement model. In this model, we combine the multivariable linear regression model with the DGM(2,1) model of Grey Prediction. At the same time, the dynamic nature of the factors that affect both supply and demand are considered in the modeling process.

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 Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
10.2991/mecs-17.2017.24
ISSN
2352-5401
DOI
10.2991/mecs-17.2017.24How 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  - Jing Tian
PY  - 2016/06
DA  - 2016/06
TI  - A Measurement Model to Determine the Ability of a Region to Provide Clean Water
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.24
DO  - 10.2991/mecs-17.2017.24
ID  - Tian2016/06
ER  -