Researches on Intelligent Parking Method of Parking Lot Based on Forecast and Multi-attribute Decision-making

DOI

10.2991/icadme-17.2017.88How to use a DOI?

Keywords

Prediction, Multiple Attribute Decision Making, Improved BP Neural Network, Optimal Routing

Abstract

For solving supply and demand balance between the parking space of parking lots and the car of the drivers, on the basis of analyzing time series forecasting techniques, the forecasting method using BP neural network algorithm was presented to forecast the parking lots free parking spaces, which was effective through MATLAB simulation. By analysis the drivers' main consideration about how to choose a parking space, the decision attribute matrix was identified by driving distance which was deduced through Dijkstra algorithm, walking distance was deduced through Euclidean distance and parking space environment value that was deduced through the entropy of triangular fuzzy number. Finally, using the grey correlation entropy method of MADM to sorting the effective free parking spaces, the optimal attributes of free parking spaces was the optimal free parking spaces.

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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TY  - CONF
AU  - Tianrui Zhang
AU  - Ruilin Wang
AU  - Yimeng Tang
AU  - Jin Xiang
AU  - Wei Xie
AU  - Shanshan Xu
PY  - 2017/07
DA  - 2017/07
TI  - Researches on Intelligent Parking Method of Parking Lot Based on Forecast and Multi-attribute Decision-making
BT  - Proceedings of the 2017 7th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
PB  - Atlantis Press
SP  - 464
EP  - 467
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-17.2017.88
DO  - 10.2991/icadme-17.2017.88
ID  - Zhang2017/07
ER  -