用神经网络定性地解释过程趋势

1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111) Pub Date : 1998-04-21 DOI:10.1109/KES.1998.725944

Y. Yamashita

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引用次数: 2

摘要

定性解释是将传感器的数值输出转化为符号表示的过程。这一过程是连接智能系统与现实世界的最关键途径之一。本文采用ART2神经网络对时间序列信号进行基于模式的分类，实现了定性解释。作为一个实例，成功地演示了气动输送机流型的自动分类。

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Qualitative interpretation of process trends by using neural networks

Qualitative interpretation is a process to convert numerical output of sensors into symbolic representation. This process is one of the most critical path to connect intelligent systems with real world. In this paper, qualitative interpretation is realized as pattern-based classification of time-series signal by using ART2 neural networks. As an example, automatic classification of flow patterns in a pneumatic conveyor is successfully demonstrated.

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1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)

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