نتایج جستجو برای: using fuzzy inference system fis

تعداد نتایج: 5040253  

2013
Abraham Meléndez Oscar Castillo Fevrier Valdez Jose Soria Mario Garcia

This paper describes the optimization of an integration block within the proposed navigation control system for a mobile robot. The control blocks that the integrator will combine are two Fuzzy Inference Systems (FIS) in charge of tracking and reaction control, respectively. The integrator block is called a Weighted Fuzzy Inference System (WFIS) and assigns weigh...

2010
Luis G. Martínez Antonio Rodríguez Díaz Guillermo Licea Sandoval Juan R. Castro

This paper proposes an ANFIS (Adaptive Network Based Fuzzy Inference System) Learning Approach where we have found patterns of personality types using Big Five Personality Tests for Software Engineering Roles in Software Development Project Teams as part of RAMSET (Role Assignment Methodology for Software Engineering Teams) methodology. An ANFIS model is applied to a set of role traits resultin...

2015
Hemad Zareiforoush Saeid Minaei Mohammad Reza Alizadeh Ahmad Banakar

In this research, a fuzzy inference system (FIS) coupled with image processing technique was developed as a decision-support system for qualitative grading of milled rice. Two quality indices, namely degree of milling (DOM) and percentage of broken kernels (PBK) were first graded by rice processing experts into five classes. Then, images of the same samples were captured using a machine vision ...

Journal: :Fuzzy Sets and Systems 2006
Hai-Jun Rong Narasimhan Sundararajan Guang-Bin Huang Paramasivan Saratchandran

In this paper, a Sequential Adaptive Fuzzy Inference System called SAFIS is developed based on the functional equivalence between a radial basis function network and a fuzzy inference system (FIS). In SAFIS, the concept of “Influence” of a fuzzy rule is introduced and using this the fuzzy rules are added or removed based on the input data received so far. If the input data do not warrant adding...

1993
Willfried Wienholt

This report takes advantage of Neural Networks (NN) and Fuzzy Inference Systems (FIS) in order to design a system suited to predict time series. We choose the solution of the Mackey{Glass time delay diierential equation in the chaotic domain as a sample problem. Fuzzy rules are generated from the sample data. The system performance is improved by means of Evolution Strategy (ES). The rules of t...

2012
M. Salmeri A. Mencattini M. Kakar

Purpose Respiratory motion prediction is a chaotic time series prediction problem. In this study, respiratory motion predictability from 12 traces from breast cancer patients is examined by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy System (IT2NSFLS). Methods Free breathing data curves were obtained from Real Time Position Management system (RPM ...

2011
S. M. Elbana M. A. Moustafa Hassan E. A. Zahab

The application of Artificial Intelligent approaches was introduced recently in protection of distribution networks. These approaches started with introducing Fuzzy Inference System (FIS), then using Artificial Neural Network (ANN).In this research, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) for protection of bus bars will be illustrated. The ANFIS can be viewed as a fuzzy...

2013
Balasubramanian

ABSTRACT-This paper proposed a control scheme based on fuzzy logic for a methanol water system of bubble cap distillation column. Fuzzy rule base and Inference System of fuzzy (FIS) is planned to regulate the reflux ratio (manipulated variable) to obtain the preferred product composition (methanol) for a distillation column. Comparisons are made with conventional controller and the results conf...

2003
Ron Edwards Ajith Abraham Sonja Petrovic-Lazarevic

The academic literature suggests that the extent of exporting by multinational corporation subsidiaries (MCS) depends on their product manufactured, resources, tax protection, customers and markets, involvement strategy, financial independence and suppliers’ relationship with a multinational corporation (MNC). The aim of this paper is to model the complex export pattern behaviour using a Takagi...

The paper deals with devising the combination of fuzzy inference systems (FIS) and neural networks called the adaptive network fuzzy inference system (ANFIS) to determine the forming limit diagram (FLD). In this paper, FLDs are determined experimentally for two grades of low carbon steel sheets using out-of-plane (dome) formability test. The effect of different parameters such as work hardening...

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