Adaptive traffic lights based on hybrid of neural network and genetic algorithm for reduced traffic congestion
نویسنده:
ناشر:
سال
: 2014شناسه الکترونیک: 10.1109/ITEC-AP.2014.6941260
کلیدواژه(گان): Kalman filters,battery powered vehicles,electric charge,genetic algorithms,nonlinear filters,secondary cells,SoC trajectory,electric vehicles,extended Kalman filter,genetic algorithm,lithium-ion battery,lumped parameter model,model error reduction,polarization time constant optimization,real-time battery current measurement,real-time battery voltage measurement,state-of-charge estimation,Accuracy,Batteries,Equations,Estimation,Integrated circuit modeling,Mathematical model
کالکشن
:
-
آمار بازدید
Adaptive traffic lights based on hybrid of neural network and genetic algorithm for reduced traffic congestion
Show full item record
contributor author | Kaur, T. , Agrawal, S. | |
date accessioned | 2020-03-12T19:40:04Z | |
date available | 2020-03-12T19:40:04Z | |
date issued | 2014 | |
identifier other | 6799655.pdf | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/985509 | |
format | general | |
language | English | |
publisher | IEEE | |
title | Adaptive traffic lights based on hybrid of neural network and genetic algorithm for reduced traffic congestion | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8101156 | |
subject keywords | Kalman filters | |
subject keywords | battery powered vehicles | |
subject keywords | electric charge | |
subject keywords | genetic algorithms | |
subject keywords | nonlinear filters | |
subject keywords | secondary cells | |
subject keywords | SoC trajectory | |
subject keywords | electric vehicles | |
subject keywords | extended Kalman filter | |
subject keywords | genetic algorithm | |
subject keywords | lithium-ion battery | |
subject keywords | lumped parameter model | |
subject keywords | model error reduction | |
subject keywords | polarization time constant optimization | |
subject keywords | real-time battery current measurement | |
subject keywords | real-time battery voltage measurement | |
subject keywords | state-of-charge estimation | |
subject keywords | Accuracy | |
subject keywords | Batteries | |
subject keywords | Equations | |
subject keywords | Estimation | |
subject keywords | Integrated circuit modeling | |
subject keywords | Mathematical model | |
identifier doi | 10.1109/ITEC-AP.2014.6941260 | |
journal title | ngineering and Computational Sciences (RAECS), 2014 Recent Advances in | |
filesize | 224874 | |
citations | 0 |