情境感知的推理测量

2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) Pub Date : 2013-07-15 DOI:10.1109/CIVEMSA.2013.6617402

Prapa Rattadilok, Andrei V. Petrovski

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引用次数: 6

摘要

本文提出了一种构建推理测量系统的通用方法。这些系统需要获取和处理的大量数据需要使用机器学习技术。在本研究中，开发了一种旨在增强态势感知的推理测量系统，并在模拟交通监控数据上进行了测试。在包含异常驾驶模式的数据上，对该系统中几种计算智能技术的性能进行了检查和比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Inferential measurements for situation awareness

The paper proposes a generic approach to building inferential measurement systems. The large amount of data needed to be acquired and processed by such systems necessitates the use of machine learning techniques. In this study, an inferential measurement system aimed at enhancing situation awareness has been developed and tested on simulated traffic surveillance data. The performance of several Computational Intelligence techniques within this system has been examined and compared on the data containing anomalous driving patterns.

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来源期刊

2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)

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