摘要
本文提出一种模糊神经网络算法,分析矿用卡车受损因素,采取措施降低卡车损坏的概率。首先,记录矿用卡车的用途、运输范围、途径路线、所处环境、生产商等信息,形成矿用卡车的信息集合;然后,利用模糊神经网络算法判断矿用卡车受损因素。实际应用显示,在矿用卡车用途、运输范围等条件一定的情况下,模糊神经网络算法能够准确地判断矿用卡车的受损因素。
This paper proposes a fuzzy neural network algorithm to analyze the factors causing damage to mining trucks and take measures to reduce the probability of truck damage.Firstly,record the purpose,transportation range,route,environment,manufacturer,and other information of mining trucks to form an information collection of mining trucks.Then,the fuzzy neural network algorithm is used to determine the damage factors of mining trucks.Practical applications have shown that under certain conditions such as the purpose and transportation range of mining trucks,the fuzzy neural network algorithm can accurately determine the factors causing damage to mining trucks.
作者
王飞
WANG Fei(Guoneng Beidian Shengli Energy Co.,Ltd.,Xilinhot,Inner Mongolia 026000,China)
出处
《自动化应用》
2023年第14期11-12,共2页
Automation Application
关键词
模糊神经网络
矿用卡车
诊断
fuzzy neural network
mining trucks
diagnosis
