The paper focuses on the application of neuro-fuzzy techniques in fault detection and isolation. The objective of this paper is to detect and isolate faults to an industrial gas turbine, with emphasis on faults occurred in the actuator part of the gas turbine. A neuro-fuzzy based learning and adaptation of TSK fuzzy models is used for residual generation, while for residual evaluation a neuro-f...

Development of Load sensor is done in this paper, the input output of the load sensor is taken from the optical fiber sensor and the inputs are load and displacement and output is voltage. Load sensor is implemented by using two models i.e. mamdani fuzzy model and neuro fuzzy model and both the models are simulated using MATLAB, Fuzzy logic Toolbox and the results of the two models are compared...

This paper describes a new class of neuro-fuzzy models, called Reinforcement Learning Hierarchical NeuroFuzzy Systems (RL-HNF). These models employ the BSP (Binary Space Partitioning) and Politree partitioning of the input space [Chrysanthou,1992] and have been developed in order to bypass traditional drawbacks of neuro-fuzzy systems: the reduced number of allowed inputs and the poor capacity t...

Background and aims: Depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. So, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. Use of this memory is latent in synthetic neuro-fuzzy algorithm. P...

Synchronous machine is an AC rotating machine whose speed under steady state condition is proportional to the frequency of the current in its armature. This paper presents an efficient neuro-fuzzy control of synchronous generator. It has been compared with fuzzy control and multilayer control. As evinced through the simulation results, neuro-fuzzy and type-2 are comparatively superior over the ...

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the applicatio...

Determination of the permeability coefficient is crucial for the solution of several geotechnical engineering problems such as modeling of underground flow, determination of the hydraulic properties of leachate water in waste disposal areas, calculation of the compressibility, and so on. Constant head permeability test, which is usually performed for the determination of the permeability, is ea...

Fuzzy inference systems have been applied in recent years in various medical fields due to their ability to obtain good results featuring white-box models. Adaptive Neuro-Fuzzy Inference System (ANFIS), which combines adaptive neural network capabilities with the fuzzy logic qualitative approach, has been previously used in modelling survival of breast cancer patients based on patient groups de...

The paper presents the neuro-fuzzy controller algorithm for air conditioning system. Neuro-fuzzy control combines the learning capabilities of neural networks and control capabilities of fuzzy logic control. The neurofuzzy controller for air conditioning system takes two inputs from temperature and humidity sensors and controls the compressor speed. The experimental results of the developed sys...

An evolving cascade neuro-fuzzy system and its online learning procedure are proposed in this paper. The system is based on nodes of a special type. A quality estimation process is defined by finding an optimal value of the used cluster validity index. Keywords— Evolving cascade system, neuro-fuzzy network, data stream, fuzzy clustering.