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Bidirectional Recurrent Neural Network-Based Chemical Process Fault Diagnosis

Industrial & engineering chemistry research, 2020-01, Vol.59 (2), p.824-834

2020

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A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network

Applied energy, 2019-10, Vol.251, p.113315, Article 113315

2019

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The promise of artificial intelligence in chemical engineering: Is it here, finally?

AIChE journal, 2019-02, Vol.65 (2), p.466-478

Venkatasubramanian, Venkat

2019

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Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

Applied energy, 2019-02, Vol.236, p.1078-1088

2019

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Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

Expert systems with applications, 2018-08, Vol.103, p.25-37

2018

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Deep learning based ensemble approach for probabilistic wind power forecasting

Applied energy, 2017-02, Vol.188, p.56-70

2017

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Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks

Applied energy, 2019-10, Vol.251, p.113381, Article 113381

2019

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A survey of artificial neural network in wind energy systems

Applied energy, 2018-10, Vol.228, p.1822-1836

2018

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Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus

Applied energy, 2018-07, Vol.222, p.799-811

2018

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Incentive-based demand response for smart grid with reinforcement learning and deep neural network

Applied energy, 2019-02, Vol.236, p.937-949

2019

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Dynamic Soft Sensor Development Based on Convolutional Neural Networks

Industrial & engineering chemistry research, 2019-07, Vol.58 (26), p.11521-11531

2019

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Machine learning: Overview of the recent progresses and implications for the process systems engineering field

Computers & chemical engineering, 2018-06, Vol.114, p.111-121

2018

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An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings

Mechanical systems and signal processing, 2019-05, Vol.122, p.692-706

2019

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A hybrid deep learning-based neural network for 24-h ahead wind power forecasting

Applied energy, 2019-09, Vol.250, p.530-539

2019

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Deep learning-based electroencephalography analysis: a systematic review

Journal of neural engineering, 2019-10, Vol.16 (5), p.051001-051001

2019

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Using Labeled Autoencoder to Supervise Neural Network Combined with k‑Nearest Neighbor for Visual Industrial Process Monitoring

Industrial & engineering chemistry research, 2019-06, Vol.58 (23), p.9952-9958

2019

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Artificial intelligence for fault diagnosis of rotating machinery: A review

Mechanical systems and signal processing, 2018-08, Vol.108, p.33-47

2018

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Different states of multi-block based forecast engine for price and load prediction

International journal of electrical power & energy systems, 2019-01, Vol.104, p.423-435

2019

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An Improved Bearing Fault Diagnosis Method using One-Dimensional CNN and LSTM

Strojniški vestnik - Journal of Mechanical Engineering, 2018-01

2018

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Convolutional Neural Network Based Fault Detection for Rotating Machinery

Journal of sound and vibration, 2016-09, Vol.377, p.331-345

2016

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Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization

Mechanical systems and signal processing, 2018-09, Vol.110, p.349-367

2018

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Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem

Applied energy, 2018-05, Vol.217, p.537-549

2018

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Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes

Industrial & engineering chemistry research, 2020-02, Vol.59 (6), p.2275-2290

2020

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A novel wind speed forecasting system based on hybrid data preprocessing and multi-objective optimization

Applied energy, 2018-12, Vol.231, p.301-319

2018

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Deep convolutional neural network model based chemical process fault diagnosis

Computers & chemical engineering, 2018-07, Vol.115, p.185-197

2018

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Bidirectional Recurrent Neural Network-Based Chemical Process Fault Diagnosis

A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network

The promise of artificial intelligence in chemical engineering: Is it here, finally?

Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

Deep learning based ensemble approach for probabilistic wind power forecasting

Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks

A survey of artificial neural network in wind energy systems

Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus

Incentive-based demand response for smart grid with reinforcement learning and deep neural network

Dynamic Soft Sensor Development Based on Convolutional Neural Networks

Machine learning: Overview of the recent progresses and implications for the process systems engineering field

An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings

A hybrid deep learning-based neural network for 24-h ahead wind power forecasting

Deep learning-based electroencephalography analysis: a systematic review

Using Labeled Autoencoder to Supervise Neural Network Combined with k‑Nearest Neighbor for Visual Industrial Process Monitoring

Artificial intelligence for fault diagnosis of rotating machinery: A review

Different states of multi-block based forecast engine for price and load prediction

An Improved Bearing Fault Diagnosis Method using One-Dimensional CNN and LSTM

Convolutional Neural Network Based Fault Detection for Rotating Machinery

Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization

Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem

Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes

A novel wind speed forecasting system based on hybrid data preprocessing and multi-objective optimization

Deep convolutional neural network model based chemical process fault diagnosis

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