Type-2 Fuzzy Reasoning Model and Algorithms

2007 ◽  
Author(s):  
Tao Wang ◽  
Yang Chen ◽  
Shaocheng Tong
Keyword(s):  
Fuzzy Reasoning

scholarly journals The Construction of Type-2 Fuzzy Reasoning Relations for Type-2 Fuzzy Logic Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Shan Zhao ◽  
Hongxing Li
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Reasoning ◽  
Fuzzy Relation ◽  
Fuzzy Relations ◽  
Fuzzy Logic Systems ◽  
Fuzzy Relation Equations ◽  
Logic Systems ◽  
Special Case

Type-2 fuzzy reasoning relations are the type-2 fuzzy relations obtained from a group of type-2 fuzzy reasonings by using extended t-(co)norm, which are essential for implementing type-2 fuzzy logic systems. In this paper an algorithm is provided for constructing type-2 fuzzy reasoning relations of SISO type-2 fuzzy logic systems. First, we give some properties of extended t-(co)norm and simplify the expression of type-2 fuzzy reasoning relations in accordance with different input subdomains under certain conditions. And then different techniques are discussed to solve the simplified expressions on the input subdomains by using the related methods on solving fuzzy relation equations. Besides, it is pointed out that the computation amount level of the proposed algorithm is the same as that of polynomials and the possibility of applying the proposed algorithm in the construction of type-2 fuzzy reasoning relations is illustrated on several examples. Finally, the calculation of an arbitrary extended continuous t-norm can be obtained as the special case of the proposed algorithm.

P200 and N400 Induced Aesthetic Quality Assessment of an Actor Using Type-2 Fuzzy Reasoning

2020 ◽  
Author(s):  
Mousumi Laha ◽  
Amit Konar ◽  
Madhuparna Das ◽  
Chandrima Debnath ◽  
Nandita Sengupta ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Fuzzy Reasoning ◽  
Aesthetic Quality

Research on an Improved Cellular Automata Model

2012 ◽  
Vol 160 ◽  
pp. 109-114
Author(s):  
Hong Wang ◽  
Yu Qiu Liu ◽  
Li Hui Zhou
Keyword(s):  
Fuzzy Logic ◽  
Cellular Automata ◽  
Fuzzy Reasoning ◽  
Fuzzy Rules ◽  
Cellular Automata Model ◽  
New Model ◽  
Model Based ◽  
Transition Functions ◽  
Combine Type

We introduce type-2 fuzzy reasoning to models of cellular automata, and combine type-2 fuzzy logic and classic cellular automata model to establish a new model of evolution reasoning, cellular automata model based on type-2 fuzzy logic. The key parts of cellular automata are transition functions and cell states. We fuzzify the transition functions of cellular automata into type-2 fuzzy rules, and cell states into type-2 fuzzy states too. Thus, we establish an improved cellular automata model based on type-2 fuzzy logic.

Triangular Interval Type-2 Interpolative Fuzzy Reasoning

2012 ◽  
Vol 198-199 ◽  
pp. 261-266
Author(s):  
Yang Chen ◽  
Tao Wang
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Fuzzy Reasoning ◽  
Membership Functions ◽  
Inference Models ◽  
Definition Of ◽  
Interval Type ◽  
Triangular Type

This paper first gives the definition of interval type-2 fuzzy sets,then investigates interval type-2 interpolative fuzzy reasoning under Triangular type membership functions. Two interpolative fuzzy reasoning algorithms responding to interval type-2 fuzzy inference models in the line of type-1 interpolative fuzzy reasoning algorithms are proposed.

scholarly journals Type-2 fuzzy logic controller optimized by wavelet networks for mobile robot navigation

2020 ◽  
Vol 18 (1) ◽  
pp. 326
Author(s):  
Fatma Affane ◽  
Kadda Zemalache Meguenni ◽  
Abdelhafid Omari
Keyword(s):  
Mobile Robot ◽  
Fuzzy Logic Controller ◽  
Robot Navigation ◽  
Target Position ◽  
Fuzzy Reasoning ◽  
Mobile Robot Navigation ◽  
Starting Position ◽  
Wavelet Networks ◽  
Minimum Delay

<p>In this work, we will use a new control strategy based on the integration of a type-2 fuzzy reasoning optimized by wavelet networks as part of a navigation system of a mobile robot. The proposed approach is able to facilitate the navigation task in an autonomous manner, in order to determine which commands must be sent at each moment to the mobile robot. This operation must take into account convergence towards a goal with the shortest possible path in the minimum delay between the starting position and the target position. Once the goal is reached, the robot stops. </p><p> </p>

Study on center-of-sets type-reduction of interval type-2 fuzzy logic systems with noniterative algorithms

2021 ◽  
pp. 1-8
Author(s):  
Yang Chen ◽  
Jiaxiu Yang
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Reasoning ◽  
Fuzzy Logic Systems ◽  
Simulation Experiments ◽  
Potential Value ◽  
Type Reduction ◽  
Logic Systems ◽  
Interval Type ◽  
Open Question

In recent years, interval type-2 fuzzy logic systems (IT2 FLSs) have become a hot topic for the capability of coping with uncertainties. Compared with the centroid type-reduction (TR), investigating the center-of-sets (COS) TR of IT2 FLSs is more favorable for applying IT2 FLSs. Actually, it is still an open question for comparing Karnik-Mendel (KM) types of algorithms and other types of alternative algorithms for COS TR. This paper gives the block of fuzzy reasoning, COS TR, and defuzzification of IT2 FLSs based on Nagar-Bardini (NB), Nie-Tan (NT) and Begian-Melek-Mendel (BMM) noniterative algorithms. Six simulation experiments are used to show the performances of three types of noniterative algorithms. The proposed noniterative algorithms can obtain much higher computational efficiencies compared with the KM algorithms, which give the potential value for designing T2 FLSs.

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