Results 31 to 40 of about 3,700 (193)
Applied Sciences, 2019 Complete characteristic curves of a pump turbine are fundamental for improving the modeling accuracy of the pump turbine in a pump turbine governing system.
Chu Zhang +4 more
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An online deep extreme learning machine based on forgetting mechanism
Dianzi Jishu Yingyong, 2018 The development of deep learning promotes the development of deep online learning, and online learning tends to have strong effectiveness. Based on the principle of online extreme learning machine and the principle of autoencoder of deep extreme learning
Liu Buzhong
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A Hybrid Autoencoder Network for Unsupervised Image Clustering
Algorithms, 2019 Image clustering involves the process of mapping an archive image into a cluster such that the set of clusters has the same information. It is an important field of machine learning and computer vision.
Pei-Yin Chen, Jih-Jeng Huang
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AE-CGAN Model based High Performance Network Intrusion Detection System
Applied Sciences, 2019 In this paper, a high-performance network intrusion detection system based on deep learning is proposed for situations in which there are significant imbalances between normal and abnormal traffic.
JooHwa Lee, KeeHyun Park
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An AutoEncoder and LSTM-Based Traffic Flow Prediction Method
Sensors, 2019 Smart cities can effectively improve the quality of urban life. Intelligent Transportation System (ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow plays an important role in ITSs. To improve the prediction
Wangyang Wei, Honghai Wu, Huadong Ma
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Sensors, 2023 The prediction of system degradation is very important as it serves as an important basis for the formulation of condition-based maintenance strategies.
Lin Huang, Xin Pan, Yajie Liu, Li Gong
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Holographic-(V)AE: An end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space [PDF]
Physical Review Research, 2022 Group-equivariant neural networks have emerged as a data-efficient approach to solve classification and regression tasks, while respecting the relevant symmetries of the data. However, little work has been done to extend this paradigm to the unsupervised and generative domains.
Gian Marco Visani +3 more
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Anomaly Detection for Agricultural Vehicles Using Autoencoders
Sensors, 2022 The safe in-field operation of autonomous agricultural vehicles requires detecting all objects that pose a risk of collision. Current vision-based algorithms for object detection and classification are unable to detect unknown classes of objects. In this
Esma Mujkic +4 more
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IEEE Access, 2019 Extreme learning machine is characterized by less training parameters, fast training speed, and strong generalization ability. It has been applied to obtain feature representations from the complex data in the tasks of data clustering or classification ...
Hongwei Ge +3 more
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Missing-Insensitive Short-Term Load Forecasting Leveraging Autoencoder and LSTM
IEEE Access, 2020 In most deep learning-based load forecasting, an intact dataset is required. Since many real-world datasets contain missing values for various reasons, missing imputation using deep learning is actively studied.
Kyungnam Park +3 more
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