Performance comparisons of tree-based and cell-based contact detection algorithms

被引:32
|
作者
Han, K. [1 ]
Feng, Y. T. [1 ]
Owen, D. R. J. [1 ]
机构
[1] Univ Wales Swansea, Sch Engn, Civil & Computat Engn Ctr, Swansea, W Glam, Wales
基金
英国工程与自然科学研究理事会;
关键词
algorithmic languages; simulation;
D O I
10.1108/02644400710729554
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Purpose - The main purpose of this paper is to compare the performance of three commonly used global search algorithms, namely tree-based augmented spatial digital tree, cell-based no binary search and D-cell, in the discrete element simulations. Design/methodology/approach - A large number of test cases with up to five million particles/discrete objects are employed to numerically examine the computational costs of the three search algorithms and their performance is compared. Findings - Comprehensive comparisons reveal that the D-cell is more efficient than the tree-based search algorithms for large-scale problems. The parametric study of the D-cell algorithm itself shows that the performance of the algorithm is strongly dependent on the cell dimension chosen. Research limitations/implications - The only limitation of the current work is that the tested domain shape is regular, and thus more complex domain shapes may need to be considered. Originality/value - The paper provides clear guidance regarding the possible actual computational performance of the tested search algorithms for practical applications.
引用
收藏
页码:165 / 181
页数:17
相关论文
共 50 条
  • [11] Models and algorithms of tree-based grid environment
    Lin, Wei-Wei
    Qi, De-Yu
    Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science), 2007, 35 (01): : 89 - 93
  • [12] Tree-Based Ensemble Models and Algorithms for Classification
    Tsiligaridis, J.
    2023 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION, ICAIIC, 2023, : 103 - 106
  • [13] Enhanced Tree-Based Anomaly Detection
    Karczmarek, Pawel
    Galka, Lukasz
    Dolecki, Michal
    Pedrycz, Witold
    Czerwinski, Dariusz
    Kiersztyn, Adam
    Stegierski, Rafal
    2022 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2022,
  • [14] A Comparative Analysis of Tree-based Machine Learning Algorithms for Breast Cancer Detection
    A'la, Fiddin Yusfida
    Permanasari, Adhistya Erna
    Setiawan, Noor Akhmad
    PROCEEDINGS OF 2019 12TH INTERNATIONAL CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGY AND SYSTEM (ICTS), 2019, : 55 - 59
  • [15] Classification Performance Analysis of Decision Tree-Based Algorithms with Noisy Class Variable
    Alharbi, Abdulmajeed Atiah
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2024, 2024
  • [16] Performance evaluation of tree-based structures
    Tran, N
    Le, DP
    Srinivasan, B
    Sier, B
    DATABASE AND EXPERT SYSTEMS APPLICATIONS, 1996, 1134 : 845 - 854
  • [17] Performance Analysis of Tree-Based Algorithms for Incremental High Utility Pattern Mining
    Ryang, Heungmo
    Yun, Unil
    ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING, 2017, 421 : 127 - 131
  • [18] Applications of python']python to evaluate the performance of decision tree-based boosting algorithms
    Kadiyala, Akhil
    Kumar, Ashok
    ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, 2018, 37 (02) : 618 - 623
  • [19] A tree-based approach to matchmaking algorithms for resource discovery
    Islam, Md. Rafiqul
    Islam, Md. Zahidul
    Leyla, Nazia
    INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, 2008, 18 (05) : 427 - 436
  • [20] ATM Allocation Using Decision Tree-Based Algorithms
    Yurdakul, Hazal Hasret
    Kasikci, Kerem
    Cagatay, Ilhan
    Guven, Melih
    Koras, Murat
    Akgun, Baris
    Gonen, Mehmet
    29TH IEEE CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS (SIU 2021), 2021,