Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm

Chu, Fei; Ma, Xiaoping; Wang, Fuli; Jia, Runda

doi:10.1007/s11771-015-2792-3

Cited by 6 publications

(1 citation statement)

References 21 publications

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“…However, it can also be used in Mamdani FIS. An example of the utilization of subtractive clustering in Mamdani-based FIS was shown in Chu et al (2015) [49].…”

Section: Fuzzy C-meansmentioning

confidence: 99%

Generating Clustering-Based Interval Fuzzy Type-2 Triangular and Trapezoidal Membership Functions: A Structured Literature Review

et al. 2021

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Clustering is more popular than the expert knowledge approach in Interval Fuzzy Type-2 membership function construction because it can construct membership function automatically with less time consumption. Most research proposed a two-fuzzifier fuzzy C-Means clustering method to construct Interval Fuzzy Type-2 membership function which mainly focused on producing Gaussian membership function. The other two important membership functions, triangular and trapezoidal, are constructed using the grid partitioning method. However, the method suffers a drawback of not being able to represent actual data composition in the underlying dataset. Some research proposed triangular and trapezoidal membership functions construction using readily formed Fuzzy Type-1 membership functions, which means it remains unclear how the membership functions are heuristically constructed using fuzzy C-Means outputs. The triangular and trapezoidal membership functions are important because previous works have shown that they may produce superior performance than Gaussian membership function in some applications. Therefore, this paper presents a structured literature review on generating triangular and trapezoidal Interval Fuzzy Type-2 membership functions using fuzzy C-Means. Initially, 110 related manuscripts were collected from Web of Science, Scopus, and Google Scholar. These manuscripts went through the identification, screening, eligibility, and inclusion processes, and as a result, 21 manuscripts were reviewed and discussed in this paper. To ensure that the review also covers the important components of fuzzy logic, this paper also reviews and discusses another 49 manuscripts on fuzzy calculation and operation. Furthermore, this paper also discusses the contributions of the conducted review to the body of knowledge, future research directions and challenges, with the aim to motivate the future works of constructing the methods to generate Interval Fuzzy Type-2 triangular and trapezoidal membership functions using fuzzy C-Means. The methods imply flexibility in choosing membership function type, hence increasing the effectiveness of fuzzy applications through leveraging the advantages that each of the three membership function types could provide.

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“…However, it can also be used in Mamdani FIS. An example of the utilization of subtractive clustering in Mamdani-based FIS was shown in Chu et al (2015) [49].…”

Section: Fuzzy C-meansmentioning

confidence: 99%

Generating Clustering-Based Interval Fuzzy Type-2 Triangular and Trapezoidal Membership Functions: A Structured Literature Review

et al. 2021

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Application Of Improved Hopfield Neural Network In Path Planning

Liu

2020

J. Phys.: Conf. Ser.

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A modified Hopfield neural network algorithm is proposed and applied to the path planning to solve some problems in the traditional Hopfield neural network. Firstly, the traditional A* algorithm is used to select the nodes in the search area that meet the criteria. Then, the nodes conforming to the standard are converted into neurons in the Hopfield neural network, and the stability of the network is used to iteratively select an optimal path. Experiments show that the improved Hopfield neural network algorithm can reduce the search time of path planning and improve efficiency.

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Prediction of CCPP output based on improved fuzzy analytical hierarchy process

Chu

Wang

et al. 2017

2017 29th Chinese Control and Decision Conference (CCDC)

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Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm

Cited by 6 publications

References 21 publications

Generating Clustering-Based Interval Fuzzy Type-2 Triangular and Trapezoidal Membership Functions: A Structured Literature Review

Generating Clustering-Based Interval Fuzzy Type-2 Triangular and Trapezoidal Membership Functions: A Structured Literature Review

Application Of Improved Hopfield Neural Network In Path Planning

Prediction of CCPP output based on improved fuzzy analytical hierarchy process

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