Ensemble learning with diversified base models for fault diagnosis in nuclear power plants

Online fault monitoring based on deep neural network & sliding window technique

(2020) Hanan A. Saeed et al.   PROGRESS IN NUCLEAR ENERGY

A new approach for fault diagnosis with full-scope simulator based on state information imaging in nuclear power plant

(2020) Yuantao Yao et al.   ANNALS OF NUCLEAR ENERGY

A new short-arc fitting method with high precision using Adam optimization algorithm

(2020) Zhigen Fei et al.   OPTIK

A novel reconstructed training-set SVM with roulette cooperative coevolution for financial time series classification

(2019) Luo Chao et al.   EXPERT SYSTEMS WITH APPLICATIONS

A hybrid fault diagnosis methodology with support vector machine and improved particle swarm optimization for nuclear power plants

(2019) Hang Wang et al.   ISA TRANSACTIONS

Integration of deep feature extraction and ensemble learning for outlier detection

(2019) Debasrita Chakraborty et al.   PATTERN RECOGNITION

A selective deep stacked denoising autoencoders ensemble with negative correlation learning for gearbox fault diagnosis

(2019) Jianbo Yu   COMPUTERS IN INDUSTRY

Three-way confusion matrix for classification: A measure driven view

(2019) Jianfeng Xu et al.   INFORMATION SCIENCES

Generalization in fully-connected neural networks for time series forecasting

(2019) Anastasia Borovykh et al.   Journal of Computational Science

Classification of NPPs transients using change of representation technique: A hybrid of unsupervised MSOM and supervised SVM

(2019) Khalil Moshkbar-Bakhshayesh et al.   PROGRESS IN NUCLEAR ENERGY

Novel application of multi-model ensemble learning for fault diagnosis in refrigeration systems

(2019) Zhan Zhang et al.   APPLIED THERMAL ENGINEERING

Dynamic selection of normalization techniques using data complexity measures

(2018) Sukirty Jain et al.   EXPERT SYSTEMS WITH APPLICATIONS

Research on intelligent fault diagnosis method for nuclear power plant based on correlation analysis and deep belief network

(2018) Bin-Sen Peng et al.   PROGRESS IN NUCLEAR ENERGY

Source term estimation of hazardous material releases using hybrid genetic algorithm with composite cost functions

(2018) Yan Wang et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Ensemble deep learning-based fault diagnosis of rotor bearing systems

(2018) Sai Ma et al.   COMPUTERS IN INDUSTRY

Genetic programming applied to the identification of accidents of a PWR nuclear power plant

(2018) Victor Henrique Cabral Pinheiro et al.   ANNALS OF NUCLEAR ENERGY

Smart wind speed forecasting approach using various boosting algorithms, big multi-step forecasting strategy

(2018) Yanfei Li et al.   RENEWABLE ENERGY

A method for multi-class sentiment classification based on an improved one-vs-one (OVO) strategy and the support vector machine (SVM) algorithm

(2017) Yang Liu et al.   INFORMATION SCIENCES

Fault diagnosis for rotary machinery with selective ensemble neural networks

(2017) Zhen-Ya Wang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Design of experiments and focused grid search for neural network parameter optimization

(2016) F.J. Pontes et al.   NEUROCOMPUTING

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

(2015) Radu-Emil Precup et al.   COMPUTERS IN INDUSTRY

Applications of fault detection and diagnosis methods in nuclear power plants: A review

(2011) Jianping Ma et al.   PROGRESS IN NUCLEAR ENERGY

A systematic analysis of performance measures for classification tasks

(2009) Marina Sokolova et al.   INFORMATION PROCESSING & MANAGEMENT