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  • Open Access

    ARTICLE

    A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

    Yongqiu Liu1, Shaohui Zhong2,*, Nasreen Kausar3, Chunwei Zhang4,*, Ardashir Mohammadzadeh4, Dragan Pamucar5,6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 793-812, 2024, DOI:10.32604/cmes.2023.028175 - 22 September 2023

    Abstract In this paper, a stable and adaptive sliding mode control (SMC) method for induction motors is introduced. Determining the parameters of this system has been one of the existing challenges. To solve this challenge, a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism. According to the dynamic changes of the system, in addition to the parameters of the SMC, the parameters of the type-2 fuzzy neural network are also updated online. The conditions for guaranteeing the convergence and stability of the control system are provided. In More >

  • Open Access

    ARTICLE

    Self-Tuning Parameters for Decision Tree Algorithm Based on Big Data Analytics

    Manar Mohamed Hafez1,*, Essam Eldin F. Elfakharany1, Amr A. Abohany2, Mostafa Thabet3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 943-958, 2023, DOI:10.32604/cmc.2023.034078 - 06 February 2023

    Abstract Big data is usually unstructured, and many applications require the analysis in real-time. Decision tree (DT) algorithm is widely used to analyze big data. Selecting the optimal depth of DT is time-consuming process as it requires many iterations. In this paper, we have designed a modified version of a (DT). The tree aims to achieve optimal depth by self-tuning running parameters and improving the accuracy. The efficiency of the modified (DT) was verified using two datasets (airport and fire datasets). The airport dataset has 500000 instances and the fire dataset has 600000 instances. A comparison More >

  • Open Access

    ARTICLE

    An ADRC Parameters Self-Tuning Control Strategy of Tension System Based on RBF Neural Network

    Shanhui Liu1,*, Haodi Ding1, Ziyu Wang1, Li’e Ma1, Zheng Li2

    Journal of Renewable Materials, Vol.11, No.4, pp. 1991-2014, 2023, DOI:10.32604/jrm.2022.023659 - 01 December 2022

    Abstract High precision control of substrate tension is the premise and guarantee for producing high-quality products in roll-to-roll precision coating machine. However, the complex relationships in tension system make the problems of decoupling control difficult to be solved, which has limited the improvement of tension control accuracy for the coating machine. Therefore, an ADRC parameters self-tuning decoupling strategy based on RBF neural network is proposed to improve the control accuracy of tension system in this paper. Firstly, a global coupling nonlinear model of the tension system is established according to the composition of the coating machine, More > Graphic Abstract

    An ADRC Parameters Self-Tuning Control Strategy of Tension System Based on RBF Neural Network

  • Open Access

    ARTICLE

    PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN

    WEI WANG1,#, YANRONG PEI2,#, SHUI-HUA WANG1, JUAN MANUEL GORRZ3, YU-DONG ZHANG1,*

    BIOCELL, Vol.47, No.2, pp. 373-384, 2023, DOI:10.32604/biocell.2023.025905 - 18 November 2022

    Abstract Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide, posing an unignorable threat to the global economy and human health. It is a disease caused by severe acute respiratory syndrome coronavirus 2, a single-stranded RNA virus of the genus Betacoronavirus. This virus is highly infectious and relies on its angiotensin-converting enzyme 2-receptor to enter cells. With the increase in the number of confirmed COVID-19 diagnoses, the difficulty of diagnosis due to the lack of global healthcare resources becomes increasingly apparent. Deep learning-based computer-aided diagnosis models with high generalisability can effectively alleviate this pressure.… More >

  • Open Access

    ARTICLE

    Modeling and Simulation of Two Axes Gimbal Using Fuzzy Control

    Ayman A. Aly1, Mohamed O. Elhabib2, Bassem F. Felemban1, B. Saleh1, Dac-Nhuong Le3,4,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 93-107, 2022, DOI:10.32604/cmc.2022.019681 - 24 February 2022

    Abstract The application of the guided missile seeker is to provide stability to the sensor's line of sight toward a target by isolating it from the missile motion and vibration. The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach. The paper is started by deriving the mathematical model for gimbals motion using Newton's second law, followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors More >

  • Open Access

    ARTICLE

    Nonlinear Identification and Control of Laser Welding Based on RBF Neural Networks

    Hongfei Wei1,*, Hui Zhao2, Xinlong Shi1, Shuang Liang3

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 51-65, 2022, DOI:10.32604/csse.2022.017739 - 08 October 2021

    Abstract A laser beam is a heat source with a high energy density; this technology has been rapidly developed and applied in the field of welding owing to its potential advantages, and supplements traditional welding techniques. An in-depth analysis of its operating process could establish a good foundation for its application in China. It is widely understood that the welding process is a highly nonlinear and multi-variable coupling process; it comprises a significant number of complex processes with random uncertain factors. Because of their nonlinear mapping and self-learning characteristics, artificial neural networks (ANNs) have certain advantages… More >

  • Open Access

    ARTICLE

    Modeling the Spike Response for Adaptive Fuzzy Spiking Neurons with Application to a Fuzzy XOR

    A. M. E. Ramírez-Mendoza1

    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.3, pp. 295-311, 2018, DOI:10.3970/cmes.2018.00239

    Abstract A spike response model (SRM) based on the spikes generator circuit (SGC) of adaptive fuzzy spiking neurons (AFSNs) is developed. The SRM is simulated in MatlabTM environment. The proposed model is applied to a configuration of a fuzzy exclusive or (fuzzy XOR) operator, as an illustrative example. A description of the comparison of AFSNs with other similar methods is given. The novel method of the AFSNs is used to determine the value of the weights or parameters of the fuzzy XOR, first with dynamic weights or self-tuning parameters that adapt continuously, then with fixed weights More >

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