[HTML][HTML] Industrial process monitoring in the big data/industry 4.0 era: From detection, to diagnosis, to prognosis
MS Reis, G Gins - Processes, 2017 - mdpi.com
We provide a critical outlook of the evolution of Industrial Process Monitoring (IPM) since its
introduction almost 100 years ago. Several evolution trends that have been structuring IPM …
introduction almost 100 years ago. Several evolution trends that have been structuring IPM …
Bayesian networks with examples in R
M Scutari, JB Denis, T Choi - 2015 - academic.oup.com
Graphical models provide visual representations of the qualitative structure of our beliefs
between collections of random quantities. Bayesian Networks are directed acyclic graphical …
between collections of random quantities. Bayesian Networks are directed acyclic graphical …
[图书][B] Introduction to high-dimensional statistics
C Giraud - 2021 - taylorfrancis.com
Praise for the first edition:"[This book] succeeds singularly at providing a structured
introduction to this active field of research.… it is arguably the most accessible overview yet …
introduction to this active field of research.… it is arguably the most accessible overview yet …
Microscope: Pinpoint performance issues with causal graphs in micro-service environments
Driven by the emerging business models (eg, digital sales) and IT technologies (eg, DevOps
and Cloud computing), the architecture of software is shifting from monolithic to microservice …
and Cloud computing), the architecture of software is shifting from monolithic to microservice …
Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information
Motivation: Reconstruction of gene regulatory networks (GRNs), which explicitly represent
the causality of developmental or regulatory process, is of utmost interest and has become a …
the causality of developmental or regulatory process, is of utmost interest and has become a …
Survey on models and techniques for root-cause analysis
Automation and computer intelligence to support complex human decisions becomes
essential to manage large and distributed systems in the Cloud and IoT era. Understanding …
essential to manage large and distributed systems in the Cloud and IoT era. Understanding …
[PDF][PDF] PC algorithm for nonparanormal graphical models.
The PC algorithm uses conditional independence tests for model selection in graphical
modeling with acyclic directed graphs. In Gaussian models, tests of conditional …
modeling with acyclic directed graphs. In Gaussian models, tests of conditional …
Incorporation of process-specific structure in statistical process monitoring: A review
MS Reis, G Gins, TJ Rato - Journal of Quality Technology, 2019 - Taylor & Francis
The incorporation of process-specific structure in monitoring activities has the potential to
improve fault detection and fault diagnosis in modern industrial scenarios. By including …
improve fault detection and fault diagnosis in modern industrial scenarios. By including …
An approach for anomaly diagnosis based on hybrid graph model with logs for distributed services
Detecting runtime anomalies is very important to monitoring and maintenance of distributed
services. People often use execution logs for troubleshooting and problem diagnosis …
services. People often use execution logs for troubleshooting and problem diagnosis …
Robust graphical modeling of gene networks using classical and alternative t-distributions
M Finegold, M Drton - 2011 - projecteuclid.org
Graphical Gaussian models have proven to be useful tools for exploring network structures
based on multivariate data. Applications to studies of gene expression have generated …
based on multivariate data. Applications to studies of gene expression have generated …