The oxidative coupling of methane (OCM) performance over Na-W-Mn/SiO2 at elevated pressures has been simulated by adaptive neuro fuzzy inference system (ANFIS) using reaction data gathered in an isothermal fixed bed microreactor. In the designed neuro fuzzy models, three important parameters such as methane to oxygen ratio, gas hourly space velocity (GHSV), and reaction temperature were conside...

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) methodology for the backcalculation of airport flexible pavement layer moduli. The proposed ANFIS-based backcalculation approach employs a hybrid learning procedure to construct a non-linear input-output mapping based on qualitative aspects of human knowledge and pavement engineering experience incorporated in...

This paper presents a methodology to formulate natural language rules for an adaptive neuro-fuzzy system based on discovered knowledge, supported by prior knowledge and statistical modeling. These rules could be improved using statistical methods and neural nets. This gives clinicians a valuable tool to explore the importance of different variables and their relations in a disease and could aid...

This paper presents the application of an adaptive neuro-fuzzy logic on the development of controller for 6 Degree-of-freedom parallel manipulator known as the Stewart platform. This manipulating structure has been well-known for its use as a flight simulator. In this research, the kinematics of the Stewart platform is analyzed first and then neuro-fuzzy logic based controller for controlling l...

Solution of inverse kinematic equations is complex problem, the complexity comes from the nonlinearity of joint space and Cartesian space mapping and having multiple solution. In this work, four adaptive neurofuzzy networks ANFIS are implemented to solve the inverse kinematics of 4-DOF SCARA manipulator. The implementation of ANFIS is easy, and the simulation of it shows that it is very fast an...

Precise control of electro-hydraulic actuator (EHA) system has been an interesting subject due to its nonlinearities and uncertainties characteristics. Good control can be designed when precise model of the system is available. Linear ARX modelling has widely been applied and satisfying result has been obtained, through linearization process. The objective of this paper is to compare ARX model ...

We present a quick and straightfoward way of input selection for neuro-fuzzy modeling using ANFIS. The method is tested on two real-world problems: the non-linear regression problem of automobile MPG (miles per gallon) prediction, and the nonlinear system identi-cation using the Box and Jenkins gas furnace data 1].

The paper presents a comparison of various soft computing techniques used for filtering and enhancing speech signals. The three major techniques that fall under soft computing are neural networks, fuzzy systems and genetic algorithms. Other hybrid techniques such as neuro-fuzzy systems are also available. In general, soft computing techniques have been experimentally observed to give far superi...

This paper introduces comprehensive fast control characteristics and continuous compensation means using Adaptive Neuro-Fuzzy Inference System. Flexible AC Transmission System (FACTS) devices have been investigated and adopted in power engineering area. There are so many advantages in using FACTS devices. It can increase dynamic stability, loading capability of transmission lines, improve power...

Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating p...