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Found 8 papers, 1 papers with code
A class alignment method based on graph convolution neural network for bearing fault diagnosis in presence of missing data and changing working conditions
Bearing fault diagnosis in real-world applications has challenges such as insufficient labeled data, changing working conditions of the rotary machinery, and missing data due to multi-rate sampling of sensors.
Learning spatiotemporal features from incomplete data for traffic flow prediction using hybrid deep neural networks
This study focuses on hybrid deep neural networks to predict traffic flow in the California Freeway Performance Measurement System (PeMS) with missing values.
An Intelligent Gearbox Fault Diagnosis under Different Operating Conditions using Adversarial Domain Adaptation
Effective gearbox diagnostic procedures can assist in rotary machinery's reliable and safe operation.
Synthetic to Real Framework based on Convolutional Multi-Head Attention and Hybrid Domain Alignment
Secondly, the generalization of most proposed unsupervised fault diagnosis methods relies on labeled faulty data collected from sensors.
Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods
This paper employs a supervised machine learning (ML) algorithm to propose an integrated fault detection and diagnosis (FDD) and fault-tolerant control (FTC) strategy to detect, diagnose, and classify the grid faults and correct the input voltage before affecting the grid-connected distributed energy resources (DER) inverters.
A CNN-BiLSTM Model with Attention Mechanism for Earthquake Prediction
This model takes advantage of LSTM and CNN with an attention mechanism to better focus on effective earthquake characteristics and produce more accurate predictions.
Spatial Graph Convolutional Neural Network via Structured Subdomain Adaptation and Domain Adversarial Learning for Bearing Fault Diagnosis
Second, adversarial domain adaptation and local maximum mean discrepancy (LMMD) methods are applied concurrently to align the subdomain's distribution and reduce structure discrepancy between relevant subdomains and global domains.
A Recursive Delay Estimation Algorithm for Linear Multivariable Systems with Time-varying Delays
In this paper, we propose a method to estimate delay for discrete time linear multiple-input multiple-output systems with time-varying input delays.
