Recent advances in artificial intelligence (AI) and data analytics (DA) could provide
opportunities for the fault management and the decision-making of the urban wastewater …

Existing pieces of literature on previous studies advocate the research focus by various
researchers to reach the benchmark of energy efficiency of Wastewater Treatment Plants …

Major assumptions in computational intelligence and machine learning consist of the
availability of a historical dataset for model development, and that the resulting model will, to …

This article applies an incremental online identification algorithm to develop a set of evolving
fuzzy models (FMs) that characterize the nonlinear finger dynamics of the human hand for …

To address the issue of soft-sensing of effluent total phosphorus in wastewater treatment
processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural …

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 …

Wastewater treatment process, including multiple biochemical reactions, is a complex
industrial process with strong nonlinearity and time-varying dynamics. It is a challenge to …

The concept of ensemble learning offers a promising avenue in learning from data streams
under complex environments because it better addresses the bias and variance dilemma …

In this paper, we propose three criteria for efficient sample selection in case of data stream
regression problems within an online active learning context. The selection becomes …

Abstract Concept drift is a common and important issue in streaming data analysis and
mining. Thus far, many concept drift detection methods have been proposed but may not be …