Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants

A long-term prediction approach based on long short-term memory neural networks with automatic parameter optimization by Tree-structured Parzen Estimator and applied to time-series data of NPP steam generators

(2020) Hoang-Phuong Nguyen et al.   APPLIED SOFT COMPUTING

An ensemble long short-term memory neural network for hourly PM2.5 concentration forecasting

(2019) Yun Bai et al.   CHEMOSPHERE

Optimizing echo state network with backtracking search optimization algorithm for time series forecasting

(2019) Zhigang Wang et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition

(2019) Ümit Çavuş Büyükşahin et al.   NEUROCOMPUTING

Prediction of short-term wind and wave conditions for marine operations using a multi-step-ahead decomposition-ANFIS model and quantification of its uncertainty

(2019) Mengning Wu et al.   OCEAN ENGINEERING

Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms

(2019) Sujan Ghimire et al.   APPLIED ENERGY

Hybrid structures in time series modeling and forecasting: A review

(2019) Zahra Hajirahimi et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Multistep Prediction of Dynamic Systems With Recurrent Neural Networks

(2019) Nima Mohajerin et al.   IEEE Transactions on Neural Networks and Learning Systems

ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module

(2018) Yujin Baek et al.   EXPERT SYSTEMS WITH APPLICATIONS

Time series forecasting of petroleum production using deep LSTM recurrent networks

(2018) Alaa Sagheer et al.   NEUROCOMPUTING

Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network

(2018) Zongxi Qu et al.   RENEWABLE ENERGY

Some Challenges and Opportunities in Reliability Engineering

(2016) Enrico Zio   IEEE TRANSACTIONS ON RELIABILITY

Adaptive ECG denoising using genetic algorithm-based thresholding and ensemble empirical mode decomposition

(2016) Phuong Nguyen et al.   INFORMATION SCIENCES

An adaptive online learning approach for Support Vector Regression: Online-SVR-FID

(2016) Jie Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Prediction of time series of NPP operating parameters using dynamic model based on BP neural network

(2015) Yong-kuo Liu et al.   ANNALS OF NUCLEAR ENERGY

Development of a New Method for Forecasting Future States of NPPs Parameters in Transients

(2014) Khalil Moshkbar-Bakhshayesh et al.   IEEE TRANSACTIONS ON NUCLEAR SCIENCE

Prediction of Leak Flow Rate Using Fuzzy Neural Networks in Severe Post-LOCA Circumstances

(2014) Dong Yeong Kim et al.   IEEE TRANSACTIONS ON NUCLEAR SCIENCE

Benefits and Challenges of System Prognostics

(2012) Bo Sun et al.   IEEE TRANSACTIONS ON RELIABILITY

Connexionist-Systems-Based Long Term Prediction Approaches for Prognostics

(2012) R. Gouriveau et al.   IEEE TRANSACTIONS ON RELIABILITY

Prediction of Axial DNBR Distribution in a Hot Fuel Rod Using Support Vector Regression Models

(2011) Dong Su Kim et al.   IEEE TRANSACTIONS ON NUCLEAR SCIENCE