نتایج جستجو برای: iterative fuzzy rule

تعداد نتایج: 300624  

Journal: :پژوهش های علوم و صنایع غذایی ایران 0
mahmoud sadeghi masoud yavarmanesh mostafa shahidi nojhabi

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

Journal: :IEEE Transactions on Fuzzy Systems 2022

Granularrules have been extensively used for classification in fuzzy datasets to promote the advancement of artificial intelligence. However, due diversity data types, how improve readability extracted granular rules while ensuring efficiency is always a challenge. Since reduct computing (GrC) can simplify real complex problem and dataset, this article carries out rule learning from perspective...

2012
K. Mahaboob Shareef

The proposed method develops a fuzzy rule-based classifier that was tested using features for islanding detection in distributed generation. In the developed technique, the initial classification boundaries are found out by using the decision tree (DT). From the DT classification boundaries, the fuzzy membership functions (MFs) are developed and the corresponding rule base is formulated for isl...

2004
Kok Wai Wong Chun Che Fung

In most control and engineering applications, the use of fuzzy system as a way to improve the humtzn-computer interaction has becoming popular. This paper reports on the use of fuzzy system in mineral processing specifically in determining the parameter d50c of hydrocyclone. However, wit,h the inputoutput data provided to build the fuzzy rule base, it normally results in a sparse fuzzy rule bas...

Journal: :International Journal of Advanced Computer Science and Applications 2018

1999
Giovanna Castellano Anna Maria Fanelli

An adaptive method to construct compact fuzzy systems for solving pattern classiication problems is presented. The method consists of two phases: a rule identiication phase and a rule selection phase. The rule identiication phase generates fuzzy rules from numerical data through a simple fuzzy grid method, then tunes the resulting fuzzy rules by training a neuro-fuzzy network used to model the ...

Journal: :Appl. Soft Comput. 2007
Manuel Mucientes David L. Moreno Alberto Bugarín Senén Barro

The design of fuzzy controllers for the implementation of behaviors in mobile robotics is a complex and highly time-consuming task. The use of machine learning techniques, such as evolutionary algorithms or artificial neural networks for the learning of these controllers allows to automate the design process. In this paper, the automated design of a fuzzy controller using genetic algorithms for...

Journal: :Expert Syst. Appl. 2011
Richard Jayadi Oentaryo Michel Pasquier Hiok Chai Quek

Neuro-fuzzy system (NFS) and especially localized NFS are powerful rule-based methods for knowledge extraction, capable of inducing salient knowledge structures from data automatically. Contemporary localized NFSs, however, often demand large features and rules to accurately describe the overall domain data, thus degrading their interpretability and generalization traits. In light of these issu...

2009
Lazaros S. Iliadis Andonis Papaleonidas

This paper presents the design and the development of an agentbased intelligent hybrid system. The system consists of a network of interacting intelligent agents aiming not only towards real-time air pollution monitoring but towards proposing proper corrective actions as well. In this manner, the concentration of air pollutants is managed in a real-time scale and as the system is informed conti...

Journal: :IEEE Transactions on Fuzzy Systems 2017

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