Study on Centroid Type-Reduction of Interval Type-2 Fuzzy Logic Systems Based on Noniterative Algorithms

Chen, Yang

doi:10.1155/2019/7325053

Cited by 20 publications

(16 citation statements)

References 48 publications

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“…In this regard, IT2FLS, characterized by MFs that are themselves fuzzy, therefore, in case there are difficulties in the determination of membership grade even as a crisp number in [0, 1], type-2 fuzzy sets are then adequate to use. So far, IT2FLSs have been used in different areas to deal with high uncertainty, non-linearity and time-varying behavior [34], including computing with words [35], intelligent controllers [36], pattern recognition [37]. A typical IT2FLS consists of five parts as fuzzifier, rule base, inference engine, type-reducer, and defuzzifier.…”

Section: Type-2 Fuzzy Logic Systemmentioning

confidence: 99%

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Improved Rapid Visual Earthquake Hazard Safety Evaluation of Existing Buildings Using a Type-2 Fuzzy Logic Model

Harirchian

Lahmer

2020

Applied Sciences

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Rapid Visual Screening (RVS) is a procedure that estimates structural scores for buildings and prioritizes their retrofit and upgrade requirements. Despite the speed and simplicity of RVS, many of the collected parameters are non-commensurable and include subjectivity due to visual observations. This might cause uncertainties in the evaluation, which emphasizes the use of a fuzzy-based method. This study aims to propose a novel RVS methodology based on the interval type-2 fuzzy logic system (IT2FLS) to set the priority of vulnerable building to undergo detailed assessment while covering uncertainties and minimizing their effects during evaluation. The proposed method estimates the vulnerability of a building, in terms of Damage Index, considering the number of stories, age of building, plan irregularity, vertical irregularity, building quality, and peak ground velocity, as inputs with a single output variable. Applicability of the proposed method has been investigated using a post-earthquake damage database of reinforced concrete buildings from the Bingöl and Düzce earthquakes in Turkey.

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Section: Type-2 Fuzzy Logic Systemmentioning

confidence: 99%

“…There are two types of T2FLSs as Mamdani and Takagi-Sugeno [34]. Here the focus is on Mamdani-type as it is more popular than Takagi-Sugeno.…”

Section: Type-2 Fuzzy Logic Systemmentioning

confidence: 99%

Improved Rapid Visual Earthquake Hazard Safety Evaluation of Existing Buildings Using a Type-2 Fuzzy Logic Model

Harirchian

Lahmer

2020

Applied Sciences

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“…Similar to the continuous KM (or EKM) algorithms [21], [23], [31], [32], the CNT algorithms can be extended to compute the centroids of GT2 FSs based on the α-planes representation theory.…”

Section: C(rãmentioning

confidence: 99%

Study on Sampling Based Discrete Nie-Tan Algorithms for Computing the Centroids of General Type-2 Fuzzy Sets

Chen

2019

IEEE Access

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General type-2 fuzzy logic systems (GT2 FLSs) have become a hot topic in current academic field. Computing the centroids of general type-2 fuzzy sets (also called type-reduction) is a central block in GT2 FLSs. Recent studies prove the continuous Nie-Tan (CNT) algorithms to be actually an accurate approach to calculate the centroids of interval type-2 fuzzy sets (IT2 FSs). This paper compares the sum operation in discrete NT algorithms and the integral operation in CNT algorithms. According to the alphaplanes representation theory of general type-2 fuzzy sets (GT2 FSs), both the discrete and continuous NT algorithms can be extended to compute the centroids of GT2 FSs. Four computer simulation experiments indicate that, when the centroid type-reduced sets and defuzzified values of GT2 FSs are solved, to properly increase the number of sampling points of primary variable can make the results of discrete NT algorithms exactly approach to the accurate benchmark CNT algorithms. Furthermore, the computation efficiency of sampling based discrete NT algorithms is much higher than the CNT algorithms.INDEX TERMS General type-2 fuzzy sets, centroid, alpha-planes, sampling, Nie-Tan algorithms.

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“…In [16], the Nagar-Bardini (NB) method as an effective non-iterative method has been put forth. In [17], a comparison is made between some non-iterative algorithms.…”

Section: Introductionmentioning

confidence: 99%

An efficient non-iterative method for computing the centroid of an interval type-2 fuzzy set

Zirkohi¹,

Lin

2021

IFS

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Interval type-2 fuzzy logic systems (IT2FLSs) have better abilities to cope with uncertainties in many applications. One major drawback of IT2FLSs is the high computational cost of the iterative Karnik-Mendel (KM) algorithms in type-reduction (TR). From the practical point of view, this prevents using IT2FLS in real-world applications. To address this issue, a novel non-iterative method called Moradi-Zirkohi-Lin (MZL) TR method is proposed for computing the centroid of an IT2FLS. This makes the practical implementation of the IT2FLSs simpler. Comparative simulation results show that the proposed method outperforms the KM TR method in terms of computational burden. Besides, closer results, in terms of accuracy, to the KM TR method among the existing non-iterative TR methods are also achieved by the proposed TR method.

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Study on Centroid Type-Reduction of Interval Type-2 Fuzzy Logic Systems Based on Noniterative Algorithms

Cited by 20 publications

References 48 publications

Improved Rapid Visual Earthquake Hazard Safety Evaluation of Existing Buildings Using a Type-2 Fuzzy Logic Model

Improved Rapid Visual Earthquake Hazard Safety Evaluation of Existing Buildings Using a Type-2 Fuzzy Logic Model

Study on Sampling Based Discrete Nie-Tan Algorithms for Computing the Centroids of General Type-2 Fuzzy Sets

An efficient non-iterative method for computing the centroid of an interval type-2 fuzzy set

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