IMRAK, Erdem . Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 54, n.2, p. 103-114, november 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/artificial-neural-networks-application-in-duplextriplex-elevator-group-control-system/>. Date accessed: 19 nov. 2024. doi:http://dx.doi.org/.
Imrak, E. (2008). Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System. Strojniški vestnik - Journal of Mechanical Engineering, 54(2), 103-114. doi:http://dx.doi.org/
@article{., author = {Erdem Imrak}, title = {Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {54}, number = {2}, year = {2008}, keywords = {elevators group control systems; neural networks; backpropagation; }, abstract = {Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger service demand pattern. This paper deals with the use of artificial neural networks for the distribution of the most suitable cars to the floors by considering the passenger service demand. Artificial neural networks are applied in Duplex/Triplex group control systems for improving passenger waiting time. The back propagation algorithm is used for training neural networks. The elevator traffic analysis and simulation results are presented and compared to conventional elevator control systems.}, issn = {0039-2480}, pages = {103-114}, doi = {}, url = {https://www.sv-jme.eu/sl/article/artificial-neural-networks-application-in-duplextriplex-elevator-group-control-system/} }
Imrak, E. 2008 November 54. Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 54:2
%A Imrak, Erdem %D 2008 %T Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System %B 2008 %9 elevators group control systems; neural networks; backpropagation; %! Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System %K elevators group control systems; neural networks; backpropagation; %X Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger service demand pattern. This paper deals with the use of artificial neural networks for the distribution of the most suitable cars to the floors by considering the passenger service demand. Artificial neural networks are applied in Duplex/Triplex group control systems for improving passenger waiting time. The back propagation algorithm is used for training neural networks. The elevator traffic analysis and simulation results are presented and compared to conventional elevator control systems. %U https://www.sv-jme.eu/sl/article/artificial-neural-networks-application-in-duplextriplex-elevator-group-control-system/ %0 Journal Article %R %& 103 %P 12 %J Strojniški vestnik - Journal of Mechanical Engineering %V 54 %N 2 %@ 0039-2480 %8 2017-11-03 %7 2017-11-03
Imrak, Erdem. "Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System." Strojniški vestnik - Journal of Mechanical Engineering [Online], 54.2 (2008): 103-114. Web. 19 Nov. 2024
TY - JOUR AU - Imrak, Erdem PY - 2008 TI - Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - elevators group control systems; neural networks; backpropagation; N2 - Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger service demand pattern. This paper deals with the use of artificial neural networks for the distribution of the most suitable cars to the floors by considering the passenger service demand. Artificial neural networks are applied in Duplex/Triplex group control systems for improving passenger waiting time. The back propagation algorithm is used for training neural networks. The elevator traffic analysis and simulation results are presented and compared to conventional elevator control systems. UR - https://www.sv-jme.eu/sl/article/artificial-neural-networks-application-in-duplextriplex-elevator-group-control-system/
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TY - JOUR AU - Imrak, Erdem PY - 2017/11/03 TI - Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 54, No 2 (2008): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - elevators group control systems, neural networks, backpropagation, N2 - Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger service demand pattern. This paper deals with the use of artificial neural networks for the distribution of the most suitable cars to the floors by considering the passenger service demand. Artificial neural networks are applied in Duplex/Triplex group control systems for improving passenger waiting time. The back propagation algorithm is used for training neural networks. The elevator traffic analysis and simulation results are presented and compared to conventional elevator control systems. UR - https://www.sv-jme.eu/sl/article/artificial-neural-networks-application-in-duplextriplex-elevator-group-control-system/
Imrak, Erdem"Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 54 Number 2 (03 November 2017)
Strojniški vestnik - Journal of Mechanical Engineering 54(2008)2, 103-114
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Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger service demand pattern. This paper deals with the use of artificial neural networks for the distribution of the most suitable cars to the floors by considering the passenger service demand. Artificial neural networks are applied in Duplex/Triplex group control systems for improving passenger waiting time. The back propagation algorithm is used for training neural networks. The elevator traffic analysis and simulation results are presented and compared to conventional elevator control systems.