As different artificial intelligence (AI) techniques continue to evolve, power systems are
undergoing significant technological changes with the primary goal of reducing …

This paper proposes a novel gradient-boosting-based ensemble system with a fuzzy
regression tree (FRT) as its base component for regression tasks. FRT first initializes the rule …

In this paper, a novel self-adaptive fuzzy learning (SAFL) system is proposed for streaming
data prediction. SAFL self-learns from data streams a predictive model composed of a set of …

It is widely recognized that learning systems have to go deeper to exchange for more
powerful representational learning capabilities in order to precisely approximate nonlinear …

Electric arc furnaces (EAFs) are intended for the recycling of steel scrap. One of the more
important variables in the recycling process is the tapping temperature of the steel. Due to …

In recent years, air pollution has attracted considerable attention worldwide. As an effective
air protection method, the accurate prediction of air pollutants can help provide an early …

This article proposes a new network approach toward the implementation of Takagi–Sugeno
(T–S) fuzzy models referred to as disjunctive fuzzy neural networks (DJFNNs). The proposed …

In this article, nonlinear object of oil and gas production of oilfield pumping station is
investigated. Approach to design a classical control system is studied. The nonlinearity of …

We propose an adaptive neuro-fuzzy inference system (ANFIS) with an incremental tree
structure based on a context-based fuzzy C-means (CFCM) clustering process. ANFIS is a …

This paper proposes a dynamic evolving fuzzy system (DEFS) for streaming data prediction.
DEFS utilises the enhanced data potential and prediction errors of individual local models …