scholarly journals A New Approach of Adaptive Network-Based Fuzzy Inference System Modeling in Laser Processing-A Graphical User Interface (GUI) Based

2009 ◽  
Vol 5 (10) ◽  
pp. 704-710 ◽  
Author(s):  
Sivarao . ◽  
Peter Brevern ◽  
N.S.M. El-Tayeb
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Fuzzy Inference System ◽  
Laser Processing ◽  
Fuzzy Inference ◽  
System Modeling ◽  
Adaptive Network ◽  
Inference System ◽  
New Approach

Modelling of laser processing cut quality by an adaptive network-based fuzzy inference system

2009 ◽  
Vol 223 (10) ◽  
pp. 2369-2381 ◽  
Author(s):  
Sivarao Subramonian ◽  
P Brevern ◽  
N S M El-Tayeb ◽  
V C Vengkatesh
Keyword(s):  
Surface Roughness ◽  
Pressure Vessel ◽  
Fuzzy Inference System ◽  
Laser Processing ◽  
Intelligent Systems ◽  
Fuzzy Inference ◽  
Design Parameters ◽  
Adaptive Network ◽  
Inference System ◽  
Cut Quality

Real-world problems in precision machining now require intelligent systems that integrate knowledge, techniques, and methodologies. Intelligent systems possess human-like expertise within a specific domain to adapt themselves and to learn to do better in making decisions for an intelligent manufacturing system. An intelligent tool called adaptive network-based fuzzy inference system (ANFIS) was used to model and predict the laser cut quality of a 2.5 mm manganese—molybdenum (Mn—Mo) alloy pressure vessel plate in this article. A 3 kW CO2 laser machine with seven selected design parameters was used to carry out 128 experiments based on 2 k factorial design with single replication. Because surface roughness (Ra) was the response parameter, it was targeted to be <15 μm to meet the requirement and benchmark of the pressure vessel manufacturer who sponsored this project. The DIN 2310-5 German laser cutting of metallic materials standard and procedure was referred to for evaluating surface roughness, where experimentally obtained results were used for Ra predictive modelling. Predictions of non-linear laser processing by ANFIS were found to be extremely promising in supplying the desired output, where Ra was predicted to an excellent degree of accuracy, reaching almost 70 per cent with the experimental pure error below 30 per cent.

IMPLEMENTASI PENENTUAN ARSITEKTUR MASJID MODERN DI ACEH MENGGUNAKAN PEMODELAN SISTEM CERDAS

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Masthura Hasan ◽  
T Iqbal Faridiansyah
Keyword(s):  
Fuzzy Inference System ◽  
Architectural Design ◽  
Fuzzy Inference ◽  
Intelligent System ◽  
Selection Process ◽  
System Modeling ◽  
Inference System ◽  
Normal Limits ◽  
Roof Structure ◽  
Selection Of

Mosque architectural design is based on Islamic culture as an approach to objects and products from the Islamic community by looking at their suitability and values and basic principles of Islam that explore more creative and innovative ideas. The purpose of this system is to help the team and the community in seeing the best mosque in the top order so that the system can be used as a reference for the team and the community. The variables used in the selection of modern mosques include facilities and infrastructure, building structure, roof structure, mosque area, level of security and facilities. The system model used is a fuzzy promethee model that is used for the modern mosque selection process. Fuzzy inference assessment is used to determine the value of each variable so that the value remains at normal limits. Fuzzy values will then be included in promethee assessment aspects. The highest promethee ranking results will be made a priority for the best mosque ranking. This fuzzy inference system and promethee system can help the management team and the community in determining the selection of modern mosques in aceh in accordance with modern mosque architecture. Intelligent System Modeling System In Determining Modern Mosque Architecture in the City of Aceh, this building will be web based so that all elements of society can see the best mosque in Aceh by being assessed by all elements of modern mosque architecture.Keywords: Fuzzy inference system, Promethe, Option of  Masjid

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.

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