Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms

Czarnowski, Ireneusz; Jȩdrzejowicz, Joanna; Jędrzejowicz, Piotr

doi:10.1109/access.2020.3048104

Cited by 8 publications

(4 citation statements)

References 53 publications

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“…Figure 10 displays the structure of the RBFN. The RBFN's hidden layer utilizes a non-linear activation function, while its output layer employs a linear activation function [31,32].…”

Section: Design Of Rbfn-based Mppt Controllermentioning

confidence: 99%

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Implementation of Non-Isolated High Gain Interleaved DC-DC Converter for Fuel Cell Electric Vehicle Using ANN-Based MPPT Controller

Subbulakshmy,

Palanisamy,

Alshahrani

et al. 2024

Sustainability

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A high conversion ratio DC-DC converter is crucial for fuel cell electric vehicles (FCEV). A fuel cell-based non-isolated high gain integrated DC-DC converter for electric vehicles is proposed in this paper. The system comprises an interleaved boost converter (IBC) at the source end, a switched capacitor cell, coupled inductors, a passive clamp circuit, and a voltage multiplier circuit (VMC). Its significance is to achieve the voltage conversion gain of 12.33 at a conversion ratio of 0.45. The idea is to use a proton exchange membrane fuel cell to power electric vehicles through a high-gain DC-DC converter. The use of an ineffective MPPT can result in lower energy conversion efficiency. Thus, this system incorporates a maximum power point tracking (MPPT) controller based on a neural network, which relies on the radial basis function network (RBFN) algorithm to track the maximum power point of the PEMFC accurately. The comparative study of the fuel cell electric vehicle (FCEV) structure with the RBFN-based MPPT technique was evaluated with that of the fuzzy logic technique using the MATLAB/Simulink platform (R2021b (MATLAB 9.11)). A 1.5 kW experimental prototype is designed with a switching frequency of 10 kHz to validate the design analysis, and its pursuance is compared between RBFN and FLC-based controllers. This manuscript will be a significant contribution towards evidencing a sustainable environment.

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“…Figure 10 displays the structure of the RBFN. The RBFN's hidden layer utilizes a non-linear activation function, while its output layer employs a linear activation function [31,32].…”

Section: Design Of Rbfn-based Mppt Controllermentioning

confidence: 99%

“…Figure 10 displays the structure of the RBFN. The RBFN's hidden layer utilizes a non-linear activation function, while its output layer employs a linear activation function [31,32]. The maximum extent of power that can be drawn from the PEFM by the RBFN-based MPPT method is explored.…”

Section: Design Of Rbfn-based Mppt Controllermentioning

confidence: 99%

Implementation of Non-Isolated High Gain Interleaved DC-DC Converter for Fuel Cell Electric Vehicle Using ANN-Based MPPT Controller

Subbulakshmy,

Palanisamy,

Alshahrani

et al. 2024

Sustainability

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show abstract

“…At the same time, it has also led the field of image processing to move towards intelligence. Therefore, higher requirements are put forward for image acquisition and transmission [11][12].…”

Section: Development Trend Of Digital Mediamentioning

confidence: 99%

Digital media image automatic recognition system based on mean clustering algorithm

Wu¹

2023

Third International Conference on Computer Vision and Information Technology (CVIT 2022)

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In recent years, with the popularity of the Internet, digital media has become an indispensable part of people's life. Image acquisition equipment is widely used in daily life and work. However, due to technical problems, it can not meet the performance requirements of users. At the same time, a large number of data and information are difficult to be effectively processed, which also reduces the image quality, reduces the storage space and increases the image distortion. Therefore, it is necessary to develop new algorithms to improve these defects. Therefore, this paper designs and develops an automatic digital media image recognition system based on mean clustering algorithm. Firstly, this paper describes the concept and characteristics of digital media. Then, this paper also studies the application of mean clustering algorithm. Based on this, an automatic digital media image recognition system is designed, and the performance of the system is tested by simulation. Finally, the test results show that the algorithm can accurately identify media images. In general, the performance of the digital media image automatic recognition system based on mean clustering algorithm can meet the needs of target users.

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“…Akhtar et al [6] used fuzzy inference to predict the average monthly power generation, and their results can be used in microgrid and smart grid applications. Czarnowski et al [7] proposed similarity and fuzzy c-mean clustering based on neural network structure and verified its effectiveness. Wilamowski et al [5] trained neural networks with an extreme learning machine and an error correction algorithm and conducted a comparative study.…”

Section: Introductionmentioning

confidence: 99%

Self-Organized Fuzzy Neural Network Nonlinear System Modeling Method Based on Clustering Algorithm

Zhang

Wang

2022

Applied Sciences

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In this paper, an improved self-organizing fuzzy neural network (SOFNN-CA) based on a clustering algorithm is proposed for nonlinear systems modeling in industrial processes. In order to reduce training time and increase training speed, we combine offline learning and online identification. The unsupervised clustering algorithm is used to generate the initial centers of the network in the offline learning phase, and, in the self-organizing phase of the system, the Mahalanobis distance (MD) index and error criterion are adopted to add neurons to learn new features. A new density potential index (DPI) combined with neuron local field potential (LFP) is designed to adjust the neuron width, which further improves the network generalization. The similarity index calculated by the Gaussian error function is used to merge neurons to reduce redundancy. Meanwhile, the convergence of SOFNN-CA in the case of structural self-organization is demonstrated. Simulations and experiments results show that the proposed SOFNN-CA has a more desirable modeling accuracy and convergence speed compared with SOFNN-ALA and SOFNN-AGA.

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Designing RBFNs Structure Using Similarity-Based and Kernel-Based Fuzzy C-Means Clustering Algorithms

Cited by 8 publications

References 53 publications

Implementation of Non-Isolated High Gain Interleaved DC-DC Converter for Fuel Cell Electric Vehicle Using ANN-Based MPPT Controller

Implementation of Non-Isolated High Gain Interleaved DC-DC Converter for Fuel Cell Electric Vehicle Using ANN-Based MPPT Controller

Digital media image automatic recognition system based on mean clustering algorithm

Self-Organized Fuzzy Neural Network Nonlinear System Modeling Method Based on Clustering Algorithm

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