Adaptive traffic lights based on hybrid of neural network and genetic algorithm for reduced traffic congestion
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: 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
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Adaptive traffic lights based on hybrid of neural network and genetic algorithm for reduced traffic congestion
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| 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 | http://libsearch.um.ac.ir:80/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 |