Statistical and machine learning methods have been proposed to predict hard drive failure based on SMART attributes, and many achieve good performance.
Experiments show that the CBN model can give a health assessment under the proposed definition where drives are predicted to fail no later than their actual ...
Statistical and machine learning methods have been proposed to predict hard drive failure based on SMART attributes, and many achieve good performance.
Instead of binary classification, some prediction models [16, 28] predict the residual life of hard drives, described by a drive's health degree.
A COMBINED BAYESIAN NETWORK METHOD FOR PREDICTING DRIVE FAILURE TIMES FROM SMART ATTRIBUTES - Free download as PDF File (.pdf), Text File (.txt) or read ...
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A combined Bayesian network method for predicting drive failure times from SMART attributes. Experiments show that the CBN model can give a health assessment ...
In this paper, we propose a failure prediction method using a Bayesian Network. Our method uses the deterioration over time of a HDD, calculated via SMART ( ...
Pang, S., Jia, Y., Stones, R., Wang, G., and Liu, X., 2016, “A Combined Bayesian Network Method for Predicting Drive Failure Times from SMART Attributes,” 2016 ...
The accuracy of health degree prediction was used to test a combined Bayesian network model [16] and a recurrent neural network model [28]. Li et al. [11,12] ...
In this paper we in- vestigate the abilities of two Bayesian methods to predict disk drive failures based on measure- ments of drive internal conditions. We ...