ESTIMATION OF PASSENGER WAITING TIME IN ELEVATOR SYSTEMS WITH ARTIFICIAL NEURAL NETWORK

被引:7
|
作者
Dursun, Mahir [1 ]
机构
[1] Gazi Univ, Tech Educ Fac, Dept Elect Educ, TR-06500 Ankara, Turkey
来源
关键词
Elevator cabinet control; neural network; up peak traffic; going and arrival time; passenger waiting time;
D O I
10.1080/10798587.2010.10643067
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this study, a simulation program for elevator control system with 10 floor apartment with 300 people was prepared by using C++ builder programming language. In simulation program, the cabin was controlled with both artificial neural network (ANN) and traditional methods under 10 different variable speeds with constant acceleration. In the program, the number of passenger and their waiting times were multiplied and applied to ANN inputs as degrees of weight. Thus, the waiting time of passengers has been added to control algorithm which is different from traditional control methods. With the suggested system, the cabin was directed to floor that has the most weighted grade. Consequently, passenger's waiting time was scattered for each floor ill balanced manner. Moreover the cabin travel time and passengers waiting time have been decreased by about 18% using suggested method for tip peak traffic situation,
引用
收藏
页码:101 / 110
页数:10
相关论文
共 50 条
  • [21] Artificial neural network based estimation of sparse multipath channels in OFDM systems
    Habib Senol
    Abdur Rehman Bin Tahir
    Atilla Özmen
    Telecommunication Systems, 2021, 77 : 231 - 240
  • [22] Artificial neural network based estimation of sparse multipath channels in OFDM systems
    Senol, Habib
    Tahir, Abdur Rehman Bin
    Ozmen, Atilla
    TELECOMMUNICATION SYSTEMS, 2021, 77 (01) : 231 - 240
  • [23] Frequency estimation in wind farm integrated systems using artificial neural network
    Jiang, Wang
    Lu, Jiping
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 62 : 72 - 79
  • [24] Estimation of Vehicular Speed and Passenger Car Equivalent Under Mixed Traffic Condition Using Artificial Neural Network
    Subhadip Biswas
    Satish Chandra
    Indrajit Ghosh
    Arabian Journal for Science and Engineering, 2017, 42 : 4099 - 4110
  • [25] Estimation of Vehicular Speed and Passenger Car Equivalent Under Mixed Traffic Condition Using Artificial Neural Network
    Biswas, Subhadip
    Chandra, Satish
    Ghosh, Indrajit
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2017, 42 (09) : 4099 - 4110
  • [26] Prediction of bus passenger trip flow based on artificial neural network
    Yu, Shaoqiang
    Shang, Caiyun
    Yu, Yang
    Zhang, Shuyuan
    Yu, Wenlong
    ADVANCES IN MECHANICAL ENGINEERING, 2016, 8 (10) : 1 - 7
  • [27] Rainfall estimation using an artificial neural network
    Hsu, K
    Sorooshian, S
    Gao, XG
    Gupta, HV
    FIRST CONFERENCE ON ARTIFICIAL INTELLIGENCE, 1998, : 28 - 32
  • [28] Estimation of soil properties by an artificial neural network
    Ofrikhter, I. V.
    Ponomaryov, A. P.
    Zakharov, A. V.
    Shenkman, R. I.
    MAGAZINE OF CIVIL ENGINEERING, 2022, 110 (02):
  • [29] Camera pose estimation by an artificial neural network
    Benton, Ryan G.
    Chu, Chee-hung Henry
    NEURAL INFORMATION PROCESSING, PT 2, PROCEEDINGS, 2006, 4233 : 604 - 611
  • [30] Artificial Neural Network for LiDAL Systems
    Al-Hameed, Aubida A.
    Younus, Safwan Hafeedh
    Hussein, Ahmed Taha
    Alresheedi, Mohammed Thamer
    Elmirghani, Jaafar M. H.
    IEEE ACCESS, 2019, 7 : 109427 - 109438