2021年9月20日 · A classification technique incorporating a novel feature derivation method is proposed for predicting failure of a system or device with multivariate time series sensor data. We treat the multivariate time series sensor data as images for both visualization and computation.

2021年9月20日 · We apply the proposed method on the early predict failure of computer disk drive in order to improve storage systems availability and avoid data loss. The classification accuracy is largely...

2021年9月20日 · We apply the proposed method on the early predict failure of computer disk drive in order to improve storage systems availability and avoid data loss. The classification accuracy is largely improved with the enriched features, named smart features.

2021年9月20日 · Computer Science > Machine Learning Title: SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application to Computer Disk Driver Authors: Lanfa Frank Wang, Danjue Li (Submitted on 20 Sep 2021)

SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application to Computer Disk Driver

SFFDD：具有丰富功能的深度神经网络，用于故障预测及其在计算机磁盘驱动程序中的应用 提出了一种结合新颖特征推导方法的分类技术，用于预测具有多变量时间序列传感器数据的系统或设备的故障。

2021年9月20日 · SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application to Computer Disk Driver. Click To Get Model/Code. A classification technique incorporating a novel feature derivation method is proposed for predicting failure of a system or device with multivariate time series sensor data.

SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application to Computer Disk Driver

Download scientific diagram | The framework of LSTM with multiple smart features. from publication: SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application...

Bibliographic details on SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application to Computer Disk Driver.