Fault detection in Tennessee Eastman process with temporal deep learning models
Automated early process fault detection and prediction remains a challenging problem in
industrial processes. Traditionally it has been done by multivariate statistical analysis of …
industrial processes. Traditionally it has been done by multivariate statistical analysis of …
Operational time-series data modeling via LSTM network integrating principal component analysis based on human experience
Today's information technologies involve increasingly intelligent systems, which come at the
cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring …
cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring …
Multivariate data quality assessment based on rotated factor scores and confidence ellipsoids
FA de Almeida, RR Leite, GF Gomes… - Decision Support …, 2020 - Elsevier
This study explores the nature of the correlation in data to estimate the data quality to be
used in decision-making processes. The main contribution of this research is the …
used in decision-making processes. The main contribution of this research is the …
A novel fuzzy comprehensive evaluation model for application effect of connected vehicle system in a tunnel scenario
S Wang, J Wen, H Li, C Rao, X Zhao - International Journal of Fuzzy …, 2022 - Springer
This paper proposes a novel fuzzy comprehensive evaluation model based on the 2-tuple
linguistic model and grey target decision method (2TL-GTD) for evaluating the …
linguistic model and grey target decision method (2TL-GTD) for evaluating the …
Statistical analysis and prediction of spatial resilient modulus of coarse-grained soils for pavement subbase and base layers using MLR, ANN and Ensemble …
CC Ikeagwuani, DC Nwonu - Innovative Infrastructure Solutions, 2022 - Springer
Prediction methods for the estimation of the resilient modulus (MR) of unbound granular
materials continues to be fraught with challenges associated with the in situ dependency of …
materials continues to be fraught with challenges associated with the in situ dependency of …
Revolutionizing agricultural stock volatility forecasting: a comparative study of machine learning and HAR-RV models
H Li, X Huang, F Luo, D Zhou, A Cao… - Journal of Applied …, 2025 - Taylor & Francis
This study investigates the realized volatility of the Shanghai Agricultural Stock Index (March
2017–May 2021), focusing on predictive accuracy. By incorporating three primary …
2017–May 2021), focusing on predictive accuracy. By incorporating three primary …
Risk assessment of block chain technology application in sports industry
X Du - 2022 international conference on wearables, sports …, 2022 - ieeexplore.ieee.org
To improve the application effect of block chain technology in sports industry, the risk
assessment is carried out for block chain technology of sports industry. Firstly, the core …
assessment is carried out for block chain technology of sports industry. Firstly, the core …