Fuzzy Rule Interpolation Research Papers (original) (raw)

Humans make use of facial expression to communicate in their day to day interactions with each other, which comes naturally without much effort. Facial expression is essentially a communication and interaction between humans and where... more

Humans make use of facial expression to communicate in their day to day interactions with each other, which comes naturally without much effort. Facial expression is essentially a communication and interaction between humans and where other information like speech is not available; it becomes what one can depend on to transmit emotion or reactions of an individual. Hence, human expression recognition with high recognition is still an interesting task. This study is aimed at implementing face detection and expression recognition using fuzzy rule interpolation (FRI) technique. This follows through a development of specifications for fuzzy rule interpolation in emotion recognition using the viola jones algorithm as the detection algorithm and local binary pattern (LBP) algorithm for the feature extraction. The extended Cohn Kanade (CK+) face database was used for the experimentation of the system. The classification of the various expressions was achieved by the image category classifier of Matlab.

In most fuzzy systems, the completeness of the fuzzy rule base is required to generate meaningful output when classical fuzzy reasoning methods are applied. This means, in other words, that the fuzzy rule base has to cover all possible... more

In most fuzzy systems, the completeness of the fuzzy rule base is required to generate meaningful output when classical fuzzy reasoning methods are applied. This means, in other words, that the fuzzy rule base has to cover all possible inputs. Regardless of the way of rule base construction, be it created by human experts or by an automated manner, often incomplete rule bases are generated. One simple solution to handle sparse fuzzy rule bases and to make infer reasonable output is the application of fuzzy rule interpolation (FRI) methods. In this paper, we present a Fuzzy Rule Interpolation Matlab Toolbox, which is freely available. With the introduction of this Matlab Toolbox, different FRI methods can be used for different real time applications, which have sparse or incomplete fuzzy rule base.

In most fuzzy systems, the completeness of the fuzzy rule base is required to generate meaningful output when classical fuzzy reasoning methods are applied. This means, in other words, that the fuzzy rule base has to cover all possible... more

In most fuzzy systems, the completeness of the fuzzy rule base is required to generate meaningful output when classical fuzzy reasoning methods are applied. This means, in other words, that the fuzzy rule base has to cover all possible inputs. Regardless of the way of rule base construction, be it created by human experts or by an automated manner, often incomplete rule bases are generated. One simple solution to handle sparse fuzzy rule bases and to make infer reasonable output is the application of fuzzy rule interpolation (FRI) methods. In this paper, we present a Fuzzy Rule Interpolation Matlab Toolbox, which is freely available. With the introduction of this Matlab Toolbox, different FRI methods can be used for different real time applications, which have sparse or incomplete fuzzy rule base.

... interpolated rule. Suppose that the number of inputs is n and the number of antecedent set Aij (jth set on input universe Xi = [mxi, Mxi]) is ni, with consequent sets Bkl,..,k, defied on output universe Y=[my,My], and rules: if Ai,ji... more

... interpolated rule. Suppose that the number of inputs is n and the number of antecedent set Aij (jth set on input universe Xi = [mxi, Mxi]) is ni, with consequent sets Bkl,..,k, defied on output universe Y=[my,My], and rules: if Ai,ji and .. and ...

The aim of this paper is to introduce a novel two-step Fuzzy Rule Interpolation Technique (FRIT) 'VEIN', based on the concept of Vague Environment. The strength of FRIT against classical fuzzy reasoning methods is the ability of... more

The aim of this paper is to introduce a novel two-step Fuzzy Rule Interpolation Technique (FRIT) 'VEIN', based on the concept of Vague Environment. The strength of FRIT against classical fuzzy reasoning methods is the ability of gaining conclusion even in case where the knowledge is represented by sparse fuzzy rule bases. The FRIT 'VEIN' introduced in this paper is

One of the most critical steps during the developmentof a fuzzy system is the identification of the fuzzy rule base andthe fuzzy partitions, the so-called “tuning”. This paper intends topresent a comparative study of three different fuzzy... more

One of the most critical steps during the developmentof a fuzzy system is the identification of the fuzzy rule base andthe fuzzy partitions, the so-called “tuning”. This paper intends topresent a comparative study of three different fuzzy partitionparameter identification methods with respect to the effect of different fuzzy partition parameterization strategies.
Keywords-fuzzy system tuning; rule base optimization; sparse rule base; fuzzy rule interpolation

Fuzzy modeling has great adaptability to thevariations of system configuration and operation conditions. This paper investigates the fuzzy modeling of a laboratory scale system of anaerobic tapered fluidized bed reactor (ATFBR). The... more

Fuzzy modeling has great adaptability to thevariations of system configuration and operation conditions. This paper investigates the fuzzy modeling of a laboratory scale system of anaerobic tapered fluidized bed reactor (ATFBR). The studied system is the anaerobic digestion of synthetic wastewater derived from the starch processing industries. The experiment was carried out in a mesophilic ATFBR reactor with mesoporous granulated activated carbon as bacterial support.The fuzzy system was generated and trained by a modified version of the Projection based Rule Extraction (PRE) method using the obtained experimental data, and it applies the inference technique Fuzzy Rule Interpolation based on Polar Cuts (FRIPOC).The output parameters predicted by the tuned system have been found to be very close to the correspondingexperimental ones and the model was validated by replicative testing. Keywords: fuzzy modeling, FRIPOC, Anaerobic Tapered Fluidized bed Reactor, OLR, COD, BOD, pH

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have... more

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have been established to solve the problems encountered by sparse rule bases. In most engineering applications, the use of more than one input variable is common.