Peak ground acceleration (PGA) plays an important role in assessing effects of earthquakes on the built environment, persons, and the natural environment. It is a basic parameter of seismic wave motion based on which earthquake resistant building design and construction are made. The level of damage is, among other factors, directly proportional to the severity of the ground acceleration, and i...

This paper presents an approach for modeling and prediction of both surface roughness and cutting zone temperature in turning of AISI304 austenitic stainless steel using multi-layer coated (TiCN+TiC+TiCN+TiN) tungsten carbide tools. The proposed approach is based on an adaptive neuro-fuzzy inference system (ANFIS) with particle swarm optimization (PSO) learning. AISI304 stainless steel bars are...

This paper analyses the operation of an adaptive neurofuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the SPV modules by changing the duty ratio of the Quasi-zsource inverter. The duty ratio of the inverter is calculated for a given solar irradiance and tem...

This paper presents sensorless rotor position estimation of Switched Reluctance Motor (SRM) where the position is to be determined by Adaptive Neuro Fuzzy Inference System (ANFIS). The rotor position sensing is very essential for the SRM for its efficient operation. Previously rotor position sensors are used to estimate the position of rotor for SRM. Due to its drawback the sensors have to be r...

This paper combines adaptive network fuzzy inference system (ANFIS) and finite element method (FEM) to study the die shape optimal design in sheet metal bending process. At first, the explicit dynamic FEM is used to simulate the sheet metal bending process. After the bending process, the springback is analyzed by using the implicit static FEM to establish the basic database for ANFIS. Then, the...

In this paper the performance of Artificial Neural Networks (ANNs) and Adaptive NeuroFuzzy Inference Systems (ANFIS) in simulating the inverse dynamic behavior of MagnetoRheological (MR) dampers is investigated. MR dampers are one of the most applicable methods in semi active control of seismic response of structures. Various mathematical models are introduced to simulate the dynamic behavior o...

This paper proposes an artificialintelligence-based solution to interface photovoltaic (PV) array with the three phase ac load and to deliver maximum power to the load. The maximum power delivery to the load is achieved by MPPT controller which employs adaptive neuro-fuzzy inference system (ANFIS). The proposed ANFIS-based MPPT offers an extremely fast dynamic response with great accuracy. The ...

Fault diagnosis of steam turbine is essential to predict further development and to anticipate it by taking appropriate measures. Fault diagnosis of modern industrial power plants by human inspection is time-consuming and expensive as well as fault diagnostic system modelling based on conventional mathematical tools is not suitable for ill defined and uncertain system. Therefore, it is necessar...

This paper investigates the ability of genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS) techniques for groundwater depth forecasting. Five different GP and ANFIS models comprising various combinations of water table depth values from two stations, Bondville and Perry, are developed to forecast one-, twoand three-day ahead water table depths. The root mean square errors...

This paper presents a new general purpose neuro-fuzzy controller to realize adaptive-network-based fuzzy inference system (ANFIS) architecture. ANFIS which tunes the fuzzy inference system with a back propagation algorithm based on collection of input-output data makes fuzzy system to learn. To implementing this idea we propose several improved CMOS analog circuits, including Gaussian-like memb...