scholarly journals RESONANT FREQUENCY CALCULATION FOR CIRCULAR MICROSTRIP ANTENNAS WITH A DIELECTRIC COVER USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM OPTIMIZED BY VARIOUS ALGORITHMS

2007 ◽  
Vol 72 ◽  
pp. 279-306 ◽  
Author(s):  
Kerim Guney ◽  
Nurcan Sarikaya
Keyword(s):  
Resonant Frequency ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Microstrip Antennas ◽  
Adaptive Network ◽  
Inference System ◽  
Frequency Calculation

scholarly journals Calculation of Resonant Frequency for a Microstrip Antenna with Vertical Slots Using Applying Adaptive Network-Based Fuzzy Inference System

2017 ◽  
Author(s):  
Mahmood Abbasi Layegh ◽  
Changiz Ghobadi ◽  
Javad Nourinia
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Resonant Frequency ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
High Approximation ◽  
Adaptive Network ◽  
Resonant Frequencies ◽  
Inference System ◽  
Artificial Neural

This paper attempts at applying adaptive network-based fuzzy inference system (ANFIS) for analysis of the resonant frequency of a microstrip rectangular patch antenna with two equal size slots which are placed on the patch vertically. The resonant frequency is calculated as the position of slots is shifted to the right and left sides on the patch. As a result , the antenna resonates at more than one frequency . Commonly, machine algorithms based on artificial neural networks are employed to recognize the whole resonant frequencies. However ,they fail to estimate the resonant frequencies correctly as in some cases variations are not very sensible and the resonant frequencies overlap each other . It can be concluded that artificial neural networks could be replaced in such designs by the adaptive network-based fuzzy Inference system due to its high approximation capability and much faster convergence rate.

Virtual fit evaluation of pants using the Adaptive Network Fuzzy Inference System

2021 ◽  
pp. 004051752110205
Author(s):  
Xueqing Zhao ◽  
Ke Fan ◽  
Xin Shi ◽  
Kaixuan Liu
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Test Accuracy ◽  
Adaptive Network ◽  
Data Set ◽  
Inference System ◽  
Second Stage ◽  
Simulated Environment ◽  
Two Stages ◽  
Fold Cross Validation

Virtual reality is a technology that allows users to completely interact with a computer-simulated environment, and put on new clothes to check the effect without taking off their clothes. In this paper, a virtual fit evaluation of pants using the Adaptive Network Fuzzy Inference System (ANFIS), VFE-ANFIS for short, is proposed. There are two stages of the VFE-ANFIS: training and evaluation. In the first stage, we trained some key pressure parameters by using the VFE-ANFIS; these key pressure parameters were collected from real try-on and virtual try-on of pants by users. In the second stage, we evaluated the fit by using the trained VFE-ANFIS, in which some key pressure parameters of pants from a new user were determined and we output the evaluation results, fit or unfit. In addition, considering the small number of input samples, we used the 10-fold cross-validation method to divide the data set into a training set and a testing set; the test accuracy of the VFE-ANFIS was 94.69% ± 2.4%, and the experimental results show that our proposed VFE-ANFIS could be applied to the virtual fit evaluation of pants.

Sign in / Sign up

Export Citation Format

Share Document