Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016)

Analysis on Green Airport Pollution Rating Model based on Analytic Hierarchy Process and Neural Network

Authors
Xin Liu
Corresponding Author
Xin Liu
Available Online September 2016.
DOI
https://doi.org/10.2991/amitp-16.2016.35How to use a DOI?
Keywords
Green Airport Pollution, Analytic Hierarchy Process, Neural Network, Analysis.
Abstract
In this paper, we conduct research on the green airport pollution rating model based on analytic hierarchy process and neural network. Environmental protection departments should summarize main airport, regional airport as soon as possible the noise characteristics and scope of reference foreign noise control experience, as soon as possible to establish sound insulation measures such as noise removal and control standards, and provide guidance for relocation and sound insulation measures. This paper combines the state-of-the-art methodologies on the corresponding research result to propose the new methodology on the modelling procedures that is innovative. We review the mathematical model for the corresponding issues to serves as the basis that is meaningful.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016)
Part of series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-245-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/amitp-16.2016.35How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xin Liu
PY  - 2016/09
DA  - 2016/09
TI  - Analysis on Green Airport Pollution Rating Model based on Analytic Hierarchy Process and Neural Network
BT  - 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016)
PB  - Atlantis Press
SP  - 179
EP  - 182
SN  - 2352-538X
UR  - https://doi.org/10.2991/amitp-16.2016.35
DO  - https://doi.org/10.2991/amitp-16.2016.35
ID  - Liu2016/09
ER  -