Simulation Experiment on Path Planning in Incomplete Fuzzy System Based on Dominance Rough Set

DOI

10.2991/amcce-15.2015.153How to use a DOI?

Keywords

Ordered information; Autonomous learning; Clustering algorithm; Rough set; Adaptability

Abstract

In order to enhance the processing capacity of the inconsistent ordered study information system and transform the rough set of different precision dominance relation, they can enhance the adaptability of inconsistent information by introducing the clustering algorithm, because rough set can effectively deal with imprecise, inconsistent and incomplete information, it can effectively get rid of dependence on a priori knowledge in the learning process, and has strong ability of independent learning. Through the simulation analysis, we found that the autonomous learning method has higher inconsistency ordered information system with the prominent advantages. In the number of different rough set, this method has different accuracy and can be very good to adapt to the change of the offensive and defensive line as well as automatic planning prevention path, which provide the theory reference for the study of basketball training autonomous learning.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Sheng Pu
PY  - 2015/04
DA  - 2015/04
TI  - Simulation Experiment on Path Planning in Incomplete Fuzzy System Based on Dominance Rough Set
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 1016
EP  - 1021
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.153
DO  - 10.2991/amcce-15.2015.153
ID  - Pu2015/04
ER  -