Selection of Minimum Rules from a Fuzzy TSK Model Using a PSO–FCM Combination

Brikh, Lamine; Guenounou, Ouahib; Bakir, Toufik

doi:10.1007/s40313-022-00975-2

Cited by 6 publications

(6 citation statements)

References 34 publications

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“…As shown in Table 1 , the OSNC method has fewer iterations and shorter searching time than the other methods (K-means 15 , FCM 21 , PSO-FCM 20 ). Experiments show that this method reduces the search time of the optimal segmentation number to a certain extent.…”

Section: Experiments and Results Analysismentioning

confidence: 99%

“…P2 : Simple and complex sample images were segmented using the K-MEANS 15 , FCM 21 and PSO-FCM 20 segmentation algorithm and the OSNC segmentation algorithm proposed in this paper. The results are shown in Figs.…”

Section: Methodsmentioning

confidence: 99%

“…Gao 19 proposed a robust fuzzy c-mean clustering method based on the adaptive elastic distance for image segmentation. Brikh 20 combined fuzzy C-means and particle swarm optimization (PSO) algorithms to cluster large nonlinear data sets.…”

Section: Introductionmentioning

confidence: 99%

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A clustering-optimized segmentation algorithm and application on food quality detection

Chen

et al. 2023

Sci Rep

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For solving the problem of quality detection in the production and processing of stuffed food, this paper suggests a small neighborhood clustering algorithm to segment the frozen dumpling image on the conveyor belt, which can effectively improve the qualified rate of food quality. This method builds feature vectors by obtaining the image's attribute parameters. The image is segmented by a distance function between categories using a small neighborhood clustering algorithm based on sample feature vectors to calculate the cluster centers. Moreover, this paper gives the selection of optimal segmentation points and sampling rate, calculates the optimal sampling rate, suggests a search method for optimal sampling rate, as well as a validity judgment function for segmentation. Optimized small neighborhood clustering (OSNC) algorithm uses the fast frozen dumpling image as a sample for continuous image target segmentation experiments. The experimental results show the accuracy of defect detection of OSNC algorithm is 95.9%. Compared with other existing segmentation algorithms, OSNC algorithm has stronger anti-interference ability, faster segmentation speed as well as more efficiently saves key information ability. It can effectively improve some disadvantages of other segmentation algorithms.

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Section: Experiments and Results Analysismentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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A clustering-optimized segmentation algorithm and application on food quality detection

Chen

et al. 2023

Sci Rep

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“…This limitation can result in suboptimal clustering solutions, as the algorithm may not always identify the best possible cluster configuration. To overcome the limitations of FCM, researchers have explored the use of global-based optimization algorithms [37][38][39].…”

Section: Fuzzy C-means Algorithmmentioning

confidence: 99%

A Novel Approach for Individual Design Perception Based on Fuzzy Inference System Training with YUKI Algorithm

Benaissa,

Kobayashi,

Kinoshita

et al. 2023

Axioms

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This paper presents a novel approach for individual design perception modeling using the YUKI algorithm-trained Fuzzy Inference System. The study focuses on understanding how individuals perceive design based on personality traits, particularly openness to experience, using the YUKI algorithm and Fuzzy C-means clustering algorithm. The approach generates several Sugeno-type Fuzzy Inference System models to predict design perception, to minimize the Root Mean Squared Error between the model prediction and the actual design perception of participants. The results demonstrate that the suggested method offers more accurate predictions compared to the traditional Fuzzy C-means Fuzzy Inference System and Deep Artificial Neural Networks, and the Root Mean Square deviation for individual design perceptions falls within a satisfactory range of 0.84 to 1.32. The YUKI algorithm-trained Fuzzy Inference System proves effective in clustering individuals based on their level of openness, providing insights into how personality traits influence design perception.

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“…The Fuzzy Tsukamoto method offers a promising approach in this regard. By leveraging fuzzy logic, this method allows for the modeling of complex and nonlinear functions [11], providing flexibility and tolerance for imprecise data [12]. Through the application of fuzzy-based classification techniques, it becomes possible to differentiate and analyze network traffic [13], enabling the detection and mitigation of ping of death attacks.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Tsukamoto-Based Detection of Ping of Death Attacks: Advancing Network Security with Precise Classification

Hawari,

Prabowo,

Adhitama

2023

IJAIDM

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Internet services have the potential to be targeted by hackers using various DDoS (Distributed Denial of Service) attack techniques, including the ping of death attack. This attack involves multiple machines launching simultaneous attacks on the database server and File Transfer Protocol (FTP), resulting in severe consequences for computer networks. To effectively classify such attacks, the Fuzzy Tsukamoto method is employed, which represents each IF-THEN rule as a Fuzzy set with a corresponding membership function. Fuzzy logic offers great flexibility, tolerance for imprecise data, and the ability to model highly complex and nonlinear functions. By implementing this classification technique, it becomes easier to differentiate and analyze network traffic captured by Wireshark, enabling the detection of ping of death attacks against the server with maximum accuracy through the Fuzzy Tsukamoto method in the classification process.

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Selection of Minimum Rules from a Fuzzy TSK Model Using a PSO–FCM Combination

Cited by 6 publications

References 34 publications

A clustering-optimized segmentation algorithm and application on food quality detection

A clustering-optimized segmentation algorithm and application on food quality detection

A Novel Approach for Individual Design Perception Based on Fuzzy Inference System Training with YUKI Algorithm

Fuzzy Tsukamoto-Based Detection of Ping of Death Attacks: Advancing Network Security with Precise Classification

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