RETRACTED: Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm (Retracted article. See vol. 2023, 2023)

被引:3
作者
Gong, Fanghai [1 ]
机构
[1] Guangzhou Huashang Vocat Coll, Sch Informat Engn, Guangzhou 511300, Peoples R China
关键词
URBAN; SIGNAL;
D O I
10.1155/2022/5178515
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to transform three-dimensional space path planning into two-dimensional plane path planning problem and greatly reduce the search time, an intelligent heuristic search algorithm based on artificial intelligence is proposed. The heuristic search algorithm is analyzed and introduced, and A is chosen. A two-dimensional spatial environment model of picking robot path planning is investigated, and a spatial model of picking robot path planning is established by raster method. Then, considering the whole day operation time, the whole day operation time is divided into several periods. With the help of heuristic search algorithm, the most reasonable operation time interval of each period is found, so as to provide reliable reference for the decision-making organization of urban rail transit operation on how to arrange the train rationally. The experimental results show that the improved A* algorithm can significantly improve the moving path of the picking robot and make the planned path smoother, which confirms the feasibility and superiority of the improved algorithm. The operation decision of urban rail transit is obtained through experiments. After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635e-001, while the average optimal value is 6.83551939e-001. After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785e-001. The average optimal value is 6.83745935e-001. After 789 iterations, the genetic algorithm obtains the optimal value of 6.83921100e-001, and the average optimal value is 6.84410765e-001. Through the comparative analysis, it can be seen that compared with the other two optimization algorithms, the heuristic search algorithm is significantly better than the other two optimization algorithms, both in terms of the optimal value and the number of optimization iterations. The results show that the heuristic search algorithm is a fast, accurate, and reliable optimization method to solve the problem of accurate scheduling of urban rail transit departure interval. It is proved that the intelligent heuristic search algorithm of artificial intelligence computer can realize the path planning effectively.
引用
收藏
页数:12
相关论文
共 25 条
  • [1] Bi-level energy optimization model in smart integrated engineering systems using WSN
    Ajay, P.
    Nagaraj, B.
    Jaya, J.
    [J]. ENERGY REPORTS, 2022, 8 : 2490 - 2495
  • [2] Design of Urban Rail Transit Network Constrained by Urban Road Network, Trips and Land-Use Characteristics
    Chai, Shushan
    Liang, Qinghuai
    Zhong, Simin
    [J]. SUSTAINABILITY, 2019, 11 (21)
  • [3] A COMPUTATION METHOD ON TIME-DEPENDENT ACCESSIBILITY OF URBAN RAIL TRANSIT NETWORKS FOR THE LAST SERVICE
    Chen, Yao
    Mao, Baohua
    Bai, Yun
    Li, Zhujun
    Tang, Jimeng
    [J]. TRANSPORT, 2020, 35 (01) : 26 - 36
  • [4] Dogra J., 2020, RECENT ADV COMPUTER, V13, P362, DOI [10.2174/2213275912666181207152633, DOI 10.2174/2213275912666181207152633]
  • [5] Current practical experience with artificial intelligence in clinical radiology: a survey of the European Society of Radiology
    Becker C.D.
    Kotter E.
    Fournier L.
    Martí-Bonmatí L.
    [J]. INSIGHTS INTO IMAGING, 2022, 13 (01)
  • [6] Will digitization, big data and artificial intelligence- and deep learning-based algorithm govern the practice of medicine?
    Goh, C. L.
    [J]. JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY, 2022, 36 (07) : 947 - 947
  • [7] Artificial intelligence to classify ear disease from otoscopy: A systematic review and meta-analysis
    Habib, Al-Rahim
    Kajbafzadeh, Majid
    Hasan, Zubair
    Wong, Eugene
    Gunasekera, Hasantha
    Perry, Chris
    Sacks, Raymond
    Kumar, Ashnil
    Singh, Narinder
    [J]. CLINICAL OTOLARYNGOLOGY, 2022, 47 (03) : 401 - 413
  • [8] Hairu Zhao, 2021, Journal of Physics: Conference Series, V1744, DOI 10.1088/1742-6596/1744/2/022032
  • [9] A heuristically self-organised Linguistic Attribute Deep Learning for edge intelligence
    He, Hongmei
    Zhu, Zhenhuan
    [J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2022, 13 (09) : 2559 - 2579
  • [10] Urban rail transit signal and control based on Internet of things
    Huang, Cong
    Huang, Ying
    [J]. JOURNAL OF HIGH SPEED NETWORKS, 2021, 27 (03) : 237 - 250