This paper discusses the application of support vector machine in the area of identification of nonlinear dynamical systems. The aim of this paper is to identify suitable model structure for nonlinear dynamic system. In this paper, Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Support Vector Regression (SVR) models are applied for identification of highly nonlinear dynamic process. The res...

The UV-spectrophotometric method of analysis was proposed for simultaneous determination of fluoxetine (FLX) and sertraline (SRT). Considering the strong spectral overlap between UV-Vis spectra of these compounds, a previous separation should be carried out in order to determine them by conventional spectrophotometric techniques. Here, full-spectrum multivariate calibrations adaptive neuro-fuzz...

This paper proposes the implementation of a very simple but efficient Adaptive Neuro-Fuzzy Inference System ( ANFIS )based algorithm to detect the edges of an gray scale image. The proposed approach begins by scanning the images using floating 3x3 pixel window. ANFIS system designed has 8 inputs, which corresponds to 8 pixels of instantaneous scanning matrix, one output that tells whether the p...

this study investigates the prediction model of compressive strength of self–compacting concrete (scc) by utilizing soft computing techniques. the techniques consist of adaptive neuro–based fuzzy inference system (anfis), artificial neural network (ann) and the hybrid of particle swarm optimization with passive congregation (psopc) and anfis called psopc–anfis. their performances are comparativ...

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ...

Abstract This study presents the development, analysis and assessment of residential lighting load profile using computational intelligence based modelling Adaptive Neuro Fuzzy Inference System (ANFIS) and Neural network (NN) models for prediction (forecasting) and evaluation of lighting load and initiatives. Factors considered in the development of the models include natural lighting, occupanc...

This paper presents an adaptive neuro-fuzzy inference system (ANFIS), which has been adapted as an alternative to other classical models for estimating the vehicle delays at signalized junctions. Rules, fuzzification, and inference were modeled by ANFIS. In this model, a hybrid algorithm was used for training and tests. The artificial network used three input variables representing simulation o...

Software Effort Prediction is the process of estimating the effort required to develop software. Effectively controlling the expensive investment of software development is achieved by accurately estimating the effort. Effort estimation at the early stage of software development is very difficult because of lot of uncertainty in input parameters which decides the software effort. Adaptive Neuro...

Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...

Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Autism spectrum disorder (ASD) neurodevelopment Clinical decision-making process complex. Due to complex nature of sign and its symptoms clinical decision making may lead misclassification. To deal with such medical problems methods or approaches soft computing play an important role. This paper will focus on presenting integ...