Realibility enhancement of a traffic signal light system using a mean-variance approach
Link to publisher's homepage at http://www.ijicic.org/home.htm
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
ICIC International
2013
|
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my/xmlui/handle/123456789/25575 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.unimap-25575 |
|---|---|
| record_format |
dspace |
| spelling |
my.unimap-255752013-05-30T06:14:42Z Realibility enhancement of a traffic signal light system using a mean-variance approach Shamshul Bahar, Yaakob Watada, Junzo Boltzmann machine Hopfield network Mean-variance analysis Structural learning Link to publisher's homepage at http://www.ijicic.org/home.htm Traffic accidents cause tragic loss of life, property damage and substantial congestion to transportation systems. A large percentage of crashes occur at or near intersections. Therefore, traffic signals are often used to improve traffic safety and operations. The objective of this study is to present a significant and effective method of determining the optimal investment involved in retrofitting signals with light emitting diode (LED) units. In this study, the reliability and risks of each unit are evaluated using a variance-covariance matrix, and the effects and expenses of replacement are analyzed. The mean-variance analysis is formulated as a mathematical program with the objectives of minimizing the risk and maximizing the expected return. Finally, a structural learning model of a mutual connection neural network is proposed to solve problems defined by mixed-integer quadratic programming, and this model is employed in the mean-variance analysis. Our method is applied to an LED signal retrofitting problem. This method enables us to select results more effectively and enhance decision-making. 2013-05-30T04:56:26Z 2013-05-30T04:56:26Z 2012-08 Article International Journal of Innovative Computing, Information and Control, vol.8 (8), 2012, pages 5835-5845. 1349-4198 http://www.ijicic.org/contents.htm http://hdl.handle.net/123456789/25575 en ICIC International |
| institution |
Universiti Malaysia Perlis |
| building |
UniMAP Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Malaysia Perlis |
| content_source |
UniMAP Library Digital Repository |
| url_provider |
http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Boltzmann machine Hopfield network Mean-variance analysis Structural learning |
| spellingShingle |
Boltzmann machine Hopfield network Mean-variance analysis Structural learning Shamshul Bahar, Yaakob Watada, Junzo Realibility enhancement of a traffic signal light system using a mean-variance approach |
| description |
Link to publisher's homepage at http://www.ijicic.org/home.htm |
| format |
Article |
| author |
Shamshul Bahar, Yaakob Watada, Junzo |
| author_facet |
Shamshul Bahar, Yaakob Watada, Junzo |
| author_sort |
Shamshul Bahar, Yaakob |
| title |
Realibility enhancement of a traffic signal light system using a mean-variance approach |
| title_short |
Realibility enhancement of a traffic signal light system using a mean-variance approach |
| title_full |
Realibility enhancement of a traffic signal light system using a mean-variance approach |
| title_fullStr |
Realibility enhancement of a traffic signal light system using a mean-variance approach |
| title_full_unstemmed |
Realibility enhancement of a traffic signal light system using a mean-variance approach |
| title_sort |
realibility enhancement of a traffic signal light system using a mean-variance approach |
| publisher |
ICIC International |
| publishDate |
2013 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/25575 |
| _version_ |
1643794699447697408 |
| score |
13.214268 |