نتایج جستجو برای: regression and anfis methods
تعداد نتایج: 16925306 فیلتر نتایج به سال:
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...
this study aimed at examining the effects of iranian efl learners’ anxiety, ambiguity tolerance, and gender on their preferences for corrective feedback (cf, henceforth). the effects were sought with regard to the necessity, frequency, and timing of cf, types of errors that need to be treated, types of cf, and choice of correctors. seventy-five iranian efl students, twenty-eight males and forty...
the purpose of this study was to find the relationship between critical thinking and self-regulation with reading comprehension of iranian female elementary language learners. the present study is a correlational one having a descriptive design. two questionnaires, critical thinking questionnaire and self-regulation questionnaire which were valid and reliable questionnaires and four reading com...
This paper presents an approach to machine fault diagnosis and condition prognosis based on classification and regression tress (CART) and neuro-fuzzy inference systems (ANFIS). In case of diagnosis, CART, which is one of the decision tree methods, is used as a feature selection tool to select pertinent features from data set and ANFIS is used as a classifier. The crisp rules obtained from CART...
In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated ...
Weather forecasting is the application of science and technology to predict the state of the atmosphere for a future time at a given location. It is carried out by collecting quantitative data about the current state of the atmosphere and past and/or present experiences. In this study Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multiple linear regression model were used to analyze metrolo...
tourism , today as one of the ways to make money, create jobs , and social and political interactions is considered. this paper aims to examine the strengths and weaknesses of tourism development in mahmoud abad ( mazandaran ). the research method in this study is " descriptive - analytical " and to collection of data used field methods such as questionnaires and documentation - library. the sa...
insurers have in the past few decades faced longevity risks - the risk that annuitants survive more than expected - and therefore need a new approach to manage this new risk. in this dissertation we survey methods that hedge longevity risks. these methods use securitization to manage risk, so using modern financial and insurance pricing models, especially wang transform and actuarial concepts, ...
abstract the current research tried to examine the impact of multiple intelligence (mi) and its components on multiple choice (mc) and open ended (oe) reading comprehension tests. ninety six students of high school in grade four took part in this study. to collect data, participants completed multiple intelligence (mi) questionnaires along with a multiple choice (mc) and open ended (oe) forms ...
This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering (ANFIS-FCM) and M5 model tree (M5Tree), for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer...
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