相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Maximum Correntropy Criterion-Based Hierarchical One-Class Classification
Jiuwen Cao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)
Structural risk minimization of rough set-based classifier
Jinfu Liu et al.
SOFT COMPUTING (2020)
Anomaly detection of gas turbines based on normal pattern extraction
Mingliang Bai et al.
APPLIED THERMAL ENGINEERING (2020)
A novel gas turbine fault detection and identification strategy based on hybrid dimensionality reduction and uncertain rule-based fuzzy logic
Shabnam Yazdani et al.
COMPUTERS IN INDUSTRY (2020)
Gas turbine performance prediction via machine learning
Zuming Liu et al.
ENERGY (2020)
Restricted-Boltzmann-Based Extreme Learning Machine for Gas Path Fault Diagnosis of Turbofan Engine
Feng Lu et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)
Applications of machine learning to machine fault diagnosis: A review and roadmap
Yaguo Lei et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)
A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings
Zuozhou Pan et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)
Array programming with NumPy
Charles R. Harris et al.
NATURE (2020)
Prediction of operating characteristics for industrial gas turbine combustor using an optimized artificial neural network
Yeseul Park et al.
ENERGY (2020)
Fault Detection for Turbine Engine Disk Based on Adaptive Weighted One-Class Support Vector Machine
Jiusheng Chen et al.
JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (2020)
Gas Path Fault Diagnosis of Aeroengine Based on Soft Square Pinball Loss ELM
Yuyuan Cao et al.
IEEE ACCESS (2020)
Probabilistic individual load forecasting using pinball loss guided LSTM
Yi Wang et al.
APPLIED ENERGY (2019)
A review of stochastic resonance in rotating machine fault detection
Siliang Lu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)
Multi-step wind speed prediction based on turbulence intensity and hybrid deep neural networks
Fei Li et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
A novel measure of attribute significance with complexity weight
Jinfu Liu et al.
APPLIED SOFT COMPUTING (2019)
Anomaly Detection in Gas Turbine Time Series by Means of Bayesian Hierarchical Models
Enzo Losi et al.
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME (2019)
A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network
Kejun Wang et al.
APPLIED ENERGY (2019)
Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine
Zhuyun Chen et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)
Aircraft engine fault detection based on grouped convolutional denoising autoencoders
Xuyun Fu et al.
CHINESE JOURNAL OF AERONAUTICS (2019)
Deep separable convolutional network for remaining useful life prediction of machinery
Biao Wang et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)
Controller Optimization Approach Using LSTM-Based Identification Model for Pumped-Storage Units
Chen Feng et al.
IEEE ACCESS (2019)
Object Classification Using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment
Hongbo Gao et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)
Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Yongzhi Zhang et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2018)
Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization
Feng Jia et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Artificial intelligence for fault diagnosis of rotating machinery: A review
Ruonan Liu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Yaguo Lei et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Fault Detection for Gas Turbine Hot Components Based on a Convolutional Neural Network
Jiao Liu et al.
ENERGIES (2018)
Non-linear system modeling using LSTM neural networks
Jesus Gonzalez et al.
IFAC PAPERSONLINE (2018)
Image spam analysis and detection
Annapurna Annadatha et al.
JOURNAL OF COMPUTER VIROLOGY AND HACKING TECHNIQUES (2018)
Gas turbine gas-path fault identification using nested artificial neural networks
Amare D. Fentaye et al.
AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY (2018)
Fading channel modelling using single-hidden layer feedforward neural networks
Junbiao Liu et al.
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING (2017)
Anomaly Detection in Gas Turbine Fuel Systems Using a Sequential Symbolic Method
Fei Li et al.
ENERGIES (2017)
A new methodology of thermodynamic diagnosis, using the thermoeconomic method together with an artificial neural network (ANN): A case study of an externally fired gas turbine (EFGT)
Dimas Jose Rua Orozco et al.
ENERGY (2017)
A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines
Mohammadreza Tahan et al.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING (2017)
Diagnosis of combined faults in Rotary Machinery by Non-Naive Bayesian approach
Mahsa Yazdanian Asr et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2017)
Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review
Mohammadreza Tahan et al.
APPLIED ENERGY (2017)
Time-frequency atoms-driven support vector machine method for bearings incipient fault diagnosis
Ruonan Liu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2016)
Gas turbine engine prognostics using Bayesian hierarchical models: A variational approach
Martha A. Zaidan et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2016)
Differential feature based hierarchical PCA fault detection method for dynamic fault
Funa Zhou et al.
NEUROCOMPUTING (2016)
Finite-sensor fault-diagnosis simulation study of gas turbine engine using information entropy and deep belief networks
De-long Feng et al.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING (2016)
Gas Turbine Fault Diagnosis Using Probabilistic Neural Networks
Igor Loboda et al.
INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES (2015)
A New Gas Path Fault Diagnostic Method of Gas Turbine Based on Support Vector Machine
Dengji Zhou et al.
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME (2015)
A Fault Diagnosis Approach for Gas Turbine Exhaust Gas Temperature Based on Fuzzy C-Means Clustering and Support Vector Machine
Zhi-tao Wang et al.
MATHEMATICAL PROBLEMS IN ENGINEERING (2015)
Real-time fault diagnosis for gas turbine generator systems using extreme learning machine
Pak Kin Wong et al.
NEUROCOMPUTING (2014)
Neural Networks for Gas Turbine Fault Identification: Multilayer Perceptron or Radial Basis Network?
Igor Loboda et al.
INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES (2012)
Mechanical fault diagnosis based on redundant second generation wavelet packet transform, neighborhood rough set and support vector machine
Ning Li et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2012)
Application of artificial neural networks to the condition monitoring and diagnosis of a combined heat and power plant
M. Fast et al.
ENERGY (2010)
A modular code for real time dynamic simulation of gas turbines in Simulink
S. M. Camporeale et al.
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME (2006)
Estimating the support of a high-dimensional distribution
B Schölkopf et al.
NEURAL COMPUTATION (2001)