This paper presents a novel adaptive neuro-fuzzy based speed controller for vector controlled induction motor drive. The proposed neuro-fuzzy controller incorporates fuzzy logic algorithm with a five-layer artificial neural network (ANN) structure. The conventional PI controller is replaced by Adaptive Neuro-Fuzzy Inference System (ANFIS), which tunes the fuzzy inference system with hybrid lear...

This work proposes a Neuro-Fuzzy Intelligent System – ANFIS (Adaptive Network based Fuzzy Inference System) for the annual forecast of greenhouse gases emissions (GHG) into the atmosphere. The purpose of this work is to apply a Neuro-Fuzzy System for annual GHG forecasting based on existing emissions data including the last 37 years in Brazil. Such emissions concern tCO2 (tons of carbon dioxide...

Fuzzy logic and fuzzy systems have recently been receiving a lot of attention, both from the media and scientific community, yet the basic techniques were originally developed in the mid-sixties. Fuzzy logic provides a formalism for implementing expert or heuristic rules on computers, and while this is the main goal in the field of expert or knowledge-based systems, fuzzy systems have had consi...

Article history: Received 20 February 2011 Accepted 4 April 2011 Available online xxxx

Maintenance plays now a critical role in manufacturing for achieving important cost savings and competitive advantage while preserving product conditions. It suggests moving from conventional maintenance practices to predictive strategy. Indeed the maintenance action has to be done at the right time based on the system performance and component Remaining Useful Life (RUL) assessed by a prognost...

Electrical conductivity is an important indicator for water quality assessment. Since the composition of mineral salts affects the electrical conductivity of groundwater, it is important to understand the relationships between mineral salt composition and electrical conductivity. In this present paper, we develop an adaptive neuro-fuzzy inference system (ANFIS) model for groundwater electrical ...

Please cite this article in press as: Talei, A., et a Expert Systems with Applications (2010), doi:10.1 Intelligent computing tools based on fuzzy logic and Artificial Neural Networks (ANN) have been successfully applied in various problems with superior performances. A new approach of combining these two powerful AI tools, known as neuro-fuzzy systems, has increasingly attracted scientists in ...

controlling a system with minimum information and regardless of dynamic equations which dominate systems is the aim of intelligent control. one of the common approaches for process control is applying shewhart's quality control charts. neuro-fuzzy networks, as one of the branches of artificial intelligence (ai), can play an effective role in the enforcement of process control's common...

Fuzzy systems can be used for function approximation based on a set of linguistic rules. We present a method to obtain the necessary parameters for such a fuzzy system by a neuro-fuzzy training method. The learning algorithm is able to determine the structure and the parameters of a fuzzy system from sample data. The approach is an extension to our already published NE-FCON and NEFCLASS models ...

We designed a neuro fuzzy control strategy for control of cyclical leg movements of paraplegic subjects. The cyclical leg movements were specified by three ‘swing phase objectives’, characteristic of natural human gait. The neuro fuzzy controller is a combination of a fuzzy logic controller and a neural network, which makes the controller self tuning and adaptive. Two experiments have been perf...