Research on remote vehicle intelligent diagnosis based on KNN

Miu Kehua; Li xiaokun

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Research on remote vehicle intelligent diagnosis based on KNN

机译：基于KNN的远程车辆智能诊断研究

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This paper provides a remote vehicle diagnosis system, which is designed to locate the specific time when an occasional malfunction happened from the abundant vehicle’s ECU data flow. The system has been designed with an ability to learn by itself, using the wrong cases to retrain the classifier and raise system diagnosis rate. Through studying the occasional low-speed flameout, we come to a conclusion that 83.3% diagnosis rate and nanosecond-class diagnosis efficiency can totally meet requirement.

机译：本文提供了一种远程车辆诊断系统，该系统可用于定位因丰富的车辆ECU数据流而偶尔发生故障的特定时间。该系统具有自我学习的能力，可以使用错误的案例重新训练分类器并提高系统诊断率。通过研究偶发的低速熄火，可以得出83.3％的诊断率和纳秒级的诊断效率完全可以满足要求。

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《BioTechnology: An Indian Journal》 |2014年第24期|共5页
作者
Miu Kehua; Li xiaokun;
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中图分类生物工程学（生物技术）;
关键词
Remote diagnosisVehicle systemKNNSelf-learningOccasional malfunction;

机译：远程诊断车辆系统KNN自学习偶尔的故障;

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Research on remote vehicle intelligent diagnosis based on KNN

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