An intelligent simulation method based on artificial neural network for container yard operation

被引：0
|
作者：
Jin, C [1 ]
Liu, XL [1 ]
Gao, P [1 ]
机构：
[1] Dalian Univ Technol, Sch Management, Dalian 116023, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 2 | 2004年 / 3174卷
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an intelligent simulation method for regulation of container yard operation on container terminal. This method includes the functions of system status evaluation, operation rule and stack height regulation, and operation scheduling. In order to realize optimal operation regulation, a control architecture based on fuzzy artificial neural network is established. The regulation process includes two phases: prediction phase forecasts coming container quantity; inference phase makes decision on operation rule and stack height. The operation scheduling is a fuzzy multi-objective programming problem with operation criteria such as minimum ship waiting time and operation time. The algorithm combining genetic algorithm with simulation is developed. A case study is presented to verify the validity and usefulness of the method in simulation environment.
引用
收藏
页码：904 / 911
页数：8
相关论文
共 50 条
  • [41] Wireless Sensor Network Simulation by Artificial Intelligent
    Khedikar, R. S.
    Kapur, A. R.
    Survanshi, Y.
    2012 2ND INTERNATIONAL CONFERENCE ON POWER, CONTROL AND EMBEDDED SYSTEMS (ICPCES 2012), 2012,
  • [42] Simulation Analysis of Automobile ABS based on Artificial Neural Network
    Chen, Banglu
    PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE, MACHINERY AND ENERGY ENGINEERING (MSMEE 2017), 2017, 123 : 1812 - 1817
  • [43] Simulation and prediction of saltwater intrusion based on artificial neural network
    Chen, Xuequn
    Li, Fulin
    Zhang, Yuchao
    Chen, Lu
    Fan, Mingyuan
    Wang, Panping
    PROCEEDINGS OF THE IAMG '07: GEOMATHEMATICS AND GIS ANALYSIS OF RESOURCES, ENVIRONMENT AND HAZARDS, 2007, : 203 - +
  • [44] Simulation of Drying Strain Based on Artificial Neural Network Model
    Fu Z.
    Cai Y.
    Gao X.
    Zhou F.
    Jiang J.
    Zhou Y.
    Zhou, Yongdong, 1600, Chinese Society of Forestry (56): : 76 - 82
  • [45] Discrete event simulation based on an artificial neural network simulator
    Möller, DPF
    Berger, A
    SIMULATION AND MODELLING: ENABLERS FOR A BETTER QUALITY OF LIFE, 2000, : 686 - 690
  • [46] Based on artificial neural network simulation of alloy finite element
    Shenyang University of Chemical Technology, Shenyang 110142, China
    Zhang, S. (shulei88@126.com), 1600, Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland (710):
  • [47] ARTIFICIAL NEURAL NETWORK BASED APPROACH TO EEG SIGNAL SIMULATION
    Tomasevic, Nikola M.
    Neskovic, Aleksandar M.
    Neskovic, Natasa J.
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2012, 22 (03)
  • [48] Agricultural Machinery Operation Posture Rapid Detection Intelligent Sensor Calibration Method Based on RBF Neural Network
    Zhang Nanfeng
    Yang Jingfeng
    Xue Yueju
    Li Zhong
    Huang Xiaolin
    MECHATRONICS, ROBOTICS AND AUTOMATION, PTS 1-3, 2013, 373-375 : 932 - +
  • [49] Euler method based route choosing strategy for the vehicles in container yard
    Li, Dong
    Wang, Ding-Wei
    Dongbei Daxue Xuebao/Journal of Northeastern University, 2009, 30 (04): : 503 - 506
  • [50] Safety analysis of aero-engine operation based on intelligent neural network
    Liu J.
    Feng Y.
    Lu C.
    Xue X.
    Pan W.
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2022, 43 (09):
12345