This study presents a new method for modeling an adaptive neuro-fuzzy inference system (ANFIS) based on vibration for predicting surface roughness in the CNC turning process. The input parameters of the model are insert nose radius, cutting speed, feed rate, depth of cut and vibration amplitude, which determine the output parameter of the surface roughness. A Gauss type membership function was ...

In this study, an adaptive neuro-fuzzy inference system (ANFIS) was developed to determine the Nusselt number (Nu) along a wavy wall in a lid-driven cavity under mixed convection regime. Firstly, the main data set of input/output vectors for training, checking and testing of the ANFIS was prepared based on the numerical results of the lattice Boltzmann method (LBM). Then, the ANFIS was develope...

Due to scarcity of fossil fuel and increasing demand of power supply, we are forced to utilize the renewable energy resources. Considering easy availability and vast potential, world has turned to solar photovoltaic energy to meet out its ever increasing energy demand. The mathematical modeling and simulation of the photovoltaic system is implemented in the MATLAB/Simulink environment and the s...

slope stability analysis is an enduring research topic in the engineering and academic sectors. accurate prediction of the factor of safety (fos) of slopes, their stability, and their performance is not an easy task. in this work, the adaptive neuro-fuzzy inference system (anfis) was utilized to build an estimation model for the prediction of fos. three anfis models were implemented including g...

This paper presents a new algorithm for building an adaptive neuro-fuzzy inference system (ANFIS) from a training data set called B-ANFIS. In order to increase accuracy of the model, the following issues are executed. Firstly, a data merging rule is proposed to build and perform a data-clustering strategy. Subsequently, a combination of clustering processes in the input data space and in the jo...

Problem statement: The statistical modeling for predicting network traffic has now become a major tool used for network and is of significant interest in many domains: Adaptive application, congestion and admission control, wireless, network management and network anomalies. To comprehend the properties of IP-network traffic and system conditions, many kinds of reports based on measured network...

Neuro-fuzzy inference systems have been used in many areas in civil engineering applications. A stability assessment model for epimetamorphic rock slopes has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS) for its capacity of dynamic nonlinear analyses. In the present study the inference system is employed to predict the stability of the slope by choosing bulk density γ, t...

In this paper, an Adaptive Neuro Fuzzy Interference System (ANFIS) is proposed for eliminating voltage harmonics present in the multilevel inverter. It is achieved by reducing the THD present in the multilevel inverter output voltage. Here, the voltage variation of the multilevel inverter is determined from the actual load voltage and the reference voltage. The voltage variation at different ti...

Due to its significance in the morphodynamic processes of natural streams and associated impacts on riverine aquatic habitats, sediment transport has been studied extensively for decades. Hydraulic researchers have endeavored to describe the above phenomenon using physical reasoning, dimensional analysis, empirical or pra ctical approaches. As a result a plethora of mathematical formulas have b...