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...

This paper presents an application of Adaptive Neuro-Fuzzy Inference System (ANFIS). The control structure of the purposed consists fuzzy logic to damp the low frequency oscillations of power system and neuro identifier to track the dynamic behavior of the plant. In practical for damping of disturbance in the power system, Automatic Voltage Controller (AVR) is used. To develop this controller a...

Navigation and obstacle avoidance in an unknown environment is proposed in this paper using hybrid neural network with fuzzy logic controller. The overall system is termed as Adaptive Neuro Fuzzy Inference System (ANFIS). ANFIS combines the benefits of fuzzy logic and neural networks for the purpose of achieving robotic navigation task. Simulation results are presented using Khepera Simulator (...

–It is difficult to identify the abnormalities in brain specially in case of Magnetic Resonance Image brain image processing. Artificial neural networks employed for brain image classification are being computationally heavy and also do not guarantee high accuracy. The major drawback of ANN is that it requires a large training set to achieve high accuracy. On the other hand fuzzy logic techniqu...

This paper discusses a fuzzy logic control system designed to determine, regulate and maintain the amount of suction needed by a robotic gripper system to perform reliable limp material manipulation. A neuro-fuzzy approach is followed to determine the amount of desired suction (depending on experimentally derived data and plant characteristics). A knowledge-based valve controller is then design...

The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the pro...

OBJECTIVE To investigate different fuzzy arithmetical operations to support in the diagnostic of epileptic events and non epileptic events. METHOD A neuro-fuzzy system was developed using the NEFCLASS (NEuro Fuzzy CLASSIfication) architecture and an artificial neural network with backpropagation learning algorithm (ANNB). RESULTS The study was composed by 244 patients with a bigger frequenc...

This paper presents a neuro-fuzzy network where all its parameters can be tuned simultaneously using Genetic Algorithms. The approach combines the merits of fuzzy logic theory, neural networks and genetic algorithms. The proposed neuro-fuzzy network does not require a priori knowledge about the system and eliminates the need for complicated design steps like manual tuning of input-output member...

This paper proposes the application of Genetic Learning as a procedure for the optimal design and training of neuro-fuzzy systems. Once this learning procedure has been implemented, hybridization between Genetic Algorithms (GA) and the traditional local search technique is carried out to form a Hybrid Algorithm, in order to achieve the maximum possible efficiency in the search, and to be able t...

Combinational Neuro-Fuzzy (NF) logic is the mixed technique generated by the combination of artificial neural network and fuzzy-logic. Various methods are proposed in the literature to restore the image degraded by impulse noise using soft computing technique where all methods have their own advantages and disadvantages. A novel idea is proposed in this paper where the ANFIS is used to detect t...