A Fuzzy Neural-Network-Driven Weighting System for Electric Shovel

被引：0
|
作者：
Gu, Yingkui [1 ]
Wu, Luheng [1 ]
Tang, Shuyun [1 ]
机构：
[1] Jiangxi Univ Sci & Technol, Sch Mech & Elect Engn, Ganzhou 341000, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2008, PT 2, PROCEEDINGS | 2008年 / 5264卷
关键词：
Fuzzy neural network; T-S model; Electric shovel; Online weighting;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to improve the weighting precision and optimize the loading of trucks and the production efficiency of electric shovel, an online weighting model is developed by using fuzzy logic and improved T-S neural network in this paper. The weighting model is established based on the mechanics analysis of the electric shovel firstly. Then, a T-S fuzzy neural network model is established to obtain the influence coefficient through training large numbers of samples. Applications show that by using the presented weighting model, it not only can decrease the fuzzy and uncertain factors in the weighting process, but also can improve the production and management efficiency.
引用
收藏
页码：526 / 532
页数：7
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