Search Results - "stack autoencoder (SAE)"

Deep Adversarial Domain Adaptation Model for Bearing Fault Diagnosis by Liu, Zhao-Hua, Lu, Bi-Liang, Wei, Hua-Liang, Chen, Lei, Li, Xiao-Hua, Ratsch, Matthias

“…Fault diagnosis of rolling bearings is an essential process for improving the reliability and safety of the rotating machinery. It is always a major challenge…”
Get full text

A Just-in-Time Fine-Tuning Framework for Deep Learning of SAE in Adaptive Data-Driven Modeling of Time-Varying Industrial Processes by Wu, Yijun, Liu, Diju, Yuan, Xiaofeng, Wang, Yalin

“…In modern industrial processes, soft sensors have played increasingly important roles for effective process monitoring, control and optimization. Deep learning…”
Get full text

SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG by Xing, Xiaofen, Li, Zhenqi, Xu, Tianyuan, Shu, Lin, Hu, Bin, Xu, Xiangmin

“… Specially, Stack AutoEncoder (SAE) is used to build and solve the linear EEG mixing model and the emotion timing model is based on the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN…”
Get full text

Damage characterization using CNN and SAE of broadband Lamb waves by Gao, Fei, Hua, Jiadong

“…) and stack autoencoder (SAE) are promising to extract features from Lamb wave signals that can be linked with damage for subsequent localization and quantification…”
Get full text

A Deep-Learning-Based Health Indicator Constructor Using Kullback–Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures by Nguyen, Tuan-Khai, Ahmad, Zahoor, Kim, Jong-Myon

“…This paper proposes a new technique for the construction of a concrete-beam health indicator based on the Kullback–Leibler divergence (KLD) and deep learning…”
Get full text

Deep learning-based protoacoustic signal denoising for proton range verification by Wang, Jing, Sohn, James J, Lei, Yang, Nie, Wei, Zhou, Jun, Avery, Stephen, Liu, Tian, Yang, Xiaofeng

“…Proton therapy is a type of radiation therapy that can provide better dose distribution compared to photon therapy by delivering most of the energy at the end…”
Get full text

A hybrid framework for predicting the remaining useful life of battery using Gaussian process regression by Li, Jiabo, Ye, Min, Wang, Yan, Wang, Qiao, Wei, Meng

“…) based on automatic stack autoencoder (SAE) and improved whale optimization algorithm (WOA) is proposed in this research paper…”
Get full text

Short-Term Streamflow Forecasting Using the Feature-Enhanced Regression Model by Bai, Yun, Bezak, Nejc, Sapač, Klaudija, Klun, Mateja, Zhang, Jin

“…), which combined stack autoencoder (SAE) with long short-term memory (LSTM). This model had two constituents…”
Get full text

A Current Signal-Based Adaptive Semisupervised Framework for Bearing Faults Diagnosis in Drivetrains by Li, Jie, Wang, Yu, Zi, Yanyang, Sun, Xiaojie, Yang, Ying

“…In most practical applications of fault diagnosis methods, two problems will inevitably arise. First, limited by the monitored object itself and its…”
Get full text

RDCSAE-RKRVFLN: A unified deep learning framework for robust and accurate DOA estimation by Raiguru, Priyadarshini, Swain, Bhanja Kishor, Rout, Susanta Kumar, Sahani, Mrutyunjaya, Mishra, Rabindra Kishore

“…) and stack autoencoder (SAE) for robust feature extraction. The RKRVFLN integrates a concise SAE output with kernel-based learning…”
Get full text

Stacked Autoencoders Driven by Semi-Supervised Learning for Building Extraction from near Infrared Remote Sensing Imagery by Protopapadakis, Eftychios, Doulamis, Anastasios, Doulamis, Nikolaos, Maltezos, Evangelos

“…In this paper, we propose a Stack Auto-encoder (SAE)-Driven and Semi-Supervised (SSL)-Based Deep Neural Network (DNN) to extract buildings from relatively…”
Get full text

Manufacturing Quality Prediction Using Intelligent Learning Approaches: A Comparative Study by Bai, Yun, Sun, Zhenzhong, Deng, Jun, Li, Lin, Long, Jianyu, Li, Chuan

“…Under the international background of the transformation and promotion of manufacturing, the Chinese government proposed the “Made in China 2025” strategy,…”
Get full text

Deep Feature Learning Architectures for Daily Reservoir Inflow Forecasting by Li, Chuan, Bai, Yun, Zeng, Bo

“…, deep restricted Boltzmann machine (DRBM) and stack Autoencoder (SAE), respectively, are introduced in this paper…”
Get full text

Power Load Forecasting System of Iron and Steel Enterprises Based on Deep Kernel–Multiple Kernel Joint Learning by Zhang, Yan, Wang, Junsheng, Sun, Jie, Sun, Ruiqi, Qin, Dawei

“…) and multiple kernel learning (MKL). The multi-kernel method was combined with the input layer, the highest coding layer, and the highest encoding layer to model the network of the stack autoencoder (SAE…”
Get full text

A Sintering State Recognition Framework to Integrate Prior Knowledge and Hidden Information Considering Class Imbalance by Wang, Dingxiang, Zhang, Xiaogang, Chen, Hua, Zhou, Yicong, Cheng, Fanyong

“… For discriminative feature extraction of imbalanced data, a cascaded stack autoencoder (SAE) model is proposed to fuse our prior knowledge and hidden information…”
Get full text

Attack classification of an intrusion detection system using deep learning and hyperparameter optimization by Kunang, Yesi Novaria, Nurmaini, Siti, Stiawan, Deris, Suprapto, Bhakti Yudho

“…A network intrusion detection system (NIDS) is a solution that mitigates the threat of attacks on a network. The success of a NIDS depends on the success of…”
Get full text

Digital Twin Inspired Intelligent Bearing Fault Diagnosis Method Based on Adaptive Correlation Filtering and Improved SAE Classification Model by Zhang, Wenhua, Liu, Zhifeng, Liao, Zhiqiang

“… In this view, this paper proposes a digital twin inspired intelligent diagnosis method for bearing faults based on adaptive correlation filtering and an improved stack autoencoder (SAE…”
Get full text

A Hybrid Forecasting System Based on Comprehensive Feature Selection and Intelligent Optimization for Stock Price Index Forecasting by He, Xuecheng, Wang, Jujie

“… Then, the stack autoencoder (SAE) algorithm is constructed to compress the feature variables…”
Get full text

Rolling Bearing Fault Diagnosis Based on Stacked Autoencoder Network with Dynamic Learning Rate by Binama, Maxime, Xu, Jin-Jun, Tang, Wei, Pan, Hong

“…Fault diagnosis is of great significance for ensuring the safety and reliable operation of rolling bearing in industries. Stack autoencoder (SAE…”
Get full text

Intrusion Detection Model Based on SAE and BALSTM by Jiajia, Fan, Jiangfeng, Xu, Junfeng, Zhang

“…, an intrusion detection model based on improved Stack autoencoder (SAE) and bidirectional feature attention short-time memory network (BALSTM) is proposed…”
Get full text