• Publications
  • Influence
Evolving fuzzy granular modeling from nonstationary fuzzy data streams
TLDR
This paper introduces an evolving fuzzy granular framework to learn from and model time-varying fuzzy input–output data streams and render singular and granular approximations of nonstationary functions. Expand
  • 87
  • 6
Fuzzy granular evolving modeling for time series prediction
TLDR
We propose fuzzy set based granular evolving modeling as a framework to learn from imprecise data streams. Expand
  • 30
  • 3
  • PDF
Top-down strategies based on adaptive fuzzy rule-based systems for daily time series forecasting
TLDR
This paper presents a data-driven approach applied to the long term prediction of daily time series in a top-down framework, thus reducing the forecast horizon from 56 to 8 steps ahead. Expand
  • 38
  • 3
Predictive fuzzy clustering model for natural streamflow forecasting
TLDR
This paper suggests a fuzzy prediction model based on fuzzy clustering as an alternative for streamflow forecast. Expand
  • 13
  • 3
OWA filters and forecasting models applied to electric power load time series
TLDR
In this paper we propose a novel approach for time series forecasting based on ordered weighted averaging operators (OWA) as linear filter and forecasting models. Expand
  • 9
  • 2
A short-term bus load forecasting system
TLDR
This paper proposes a methodology for a short-term bus load forecasting using few aggregated models. Expand
  • 13
  • 2
  • PDF
Enhanced evolving participatory learning fuzzy modeling: an application for asset returns volatility forecasting
TLDR
This paper proposes an enhanced version of the ePL approach, called ePL+, which includes both an utility measure to shrink rule bases, and a variable cluster radius mechanism to improve the cluster structure. Expand
  • 41
  • 1
Learning algorithms for a class of neurofuzzy network and application
TLDR
A class of neurofuzzy networks and a constructive, competition-based learning procedure is introduced. Expand
  • 50
  • 1
Evolving Hybrid Neural Fuzzy Network for System Modeling and Time Series Forecasting
TLDR
This paper introduces an evolving hybrid fuzzy neural network-based modeling approach using neurons based on uninorms and sigmoidal activation functions in a feed forward structure. Expand
  • 21
  • 1
Participatory Evolving Fuzzy Modeling
This paper introduces an approach to develop evolving fuzzy rule-based models based on the idea of participatory learning. Participatory learning is a means to learn and revise beliefs based on whatExpand
  • 30
  • 1