An improved code selection algorithm for fault prediction

被引:0
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作者
Yin Kuang
Zhang Yi
Lei Zhang
机构
[1] Sichuan University,Machine Intelligence Laboratory, College of Computer Science
来源
关键词
Fault prediction; Cortical learning; Sparse distributed coding; Binary code selection algorithm; SISC (similar inputs map to similar codes);
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学科分类号
摘要
The goal of this study is to present an improved code selection algorithm (BCSA) for fault prediction. The contributions mainly contain three parts. The first part is on the extension of the horizontal input in the code selection algorithm (CSA). We propose that the horizontal input is also the prediction for the next coming event, not only for recalling. Thus, BCSA is able to recall and predict alternately. The second part is on the extension of the generic minicolumnar function. We propose that the function of a minicolumn is to be a k-winner-take-all competitive module (CM) and all active cells (the overall input is 1) should be chosen as winners within a CM. The third part is on the improvement of the competition mechanism. In BCSA, the winners are directly chosen with only one round competition. Thus, computing the input’s similarity G is unnecessary. BCSA is applied to analyze the disaster of the space shuttle Challenger which is a well-known example of fault prediction. Compared to other methods, the result of BCSA is specific, robust and independent of the parameters.
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页码:1763 / 1772
页数:9
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