An overview on fault diagnosis and nature-inspired optimal control of industrial process applications
Fault detection, isolation and optimal control have long been applied to industry. These
techniques have proven various successful theoretical results and industrial applications …
techniques have proven various successful theoretical results and industrial applications …
[HTML][HTML] Autonomous learning for fuzzy systems: a review
As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
Big data analytics and application for logistics and supply chain management
This special issue explores big data analytics and applications for logistics and supply chain
management by examining novel methods, practices, and opportunities. The articles present …
management by examining novel methods, practices, and opportunities. The articles present …
Deep learning-based water quality estimation and anomaly detection using Landsat-8/Sentinel-2 virtual constellation and cloud computing
KT Peterson, V Sagan, JJ Sloan - GIScience & Remote Sensing, 2020 - Taylor & Francis
Monitoring of inland water quality is of significant importance due to the increase in water
quality related issues, especially within the Midwestern United States. Traditional monitoring …
quality related issues, especially within the Midwestern United States. Traditional monitoring …
PANFIS: A novel incremental learning machine
Most of the dynamics in real-world systems are compiled by shifts and drifts, which are
uneasy to be overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in …
uneasy to be overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in …
An incremental learning of concept drifts using evolving type-2 recurrent fuzzy neural networks
The age of online data stream and dynamic environments results in the increasing demand
of advanced machine learning techniques to deal with concept drifts in large data streams …
of advanced machine learning techniques to deal with concept drifts in large data streams …
GENEFIS: Toward an effective localist network
M Pratama, SG Anavatti… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
Nowadays, there is increasing demand for an integrated system usable to real-time
environments under limited computational resources and minimum operator supervision. In …
environments under limited computational resources and minimum operator supervision. In …
Ensemble of evolving data clouds and fuzzy models for weather time series prediction
This paper describes a variation of data cloud-based intelligent method known as typicality-
and-eccentricity-based method for data analysis (TEDA). The objective is to develop data …
and-eccentricity-based method for data analysis (TEDA). The objective is to develop data …
Implementation of an evolving fuzzy model (eFuMo) in a monitoring system for a waste-water treatment process
Increasing demands on effluent quality and loads call for an improved control, monitoring,
and fault detection of waste-water treatment plants (WWTPs). Improved control and …
and fault detection of waste-water treatment plants (WWTPs). Improved control and …
Fully unsupervised fault detection and identification based on recursive density estimation and self-evolving cloud-based classifier
In this paper, we propose a two-stage algorithm for real-time fault detection and identification
of industrial plants. Our proposal is based on the analysis of selected features using …
of industrial plants. Our proposal is based on the analysis of selected features using …