Search Results - Fractional-order backpropagation learning algorithm

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  1. 1

    A-LugSeg: Automatic and explainability-guided multi-site lung detection in chest X-ray images by Peng, Tao, Gu, Yidong, Ye, Zhenyu, Cheng, Xiuxiu, Wang, Jing

    ISSN: 0957-4174, 1873-6793
    Published: New York Elsevier Ltd 15.07.2022
    Published in Expert systems with applications (15.07.2022)
    “…•An improved machine learning model is proposed to express a mathematical model.•The explainability-guided mathematical model is used to denote lung contour…”
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    Journal Article
  2. 2

    Modeling and Control of Permanent Magnet Synchronous Motor Based Electric Vehicle by G., Rajesh, Sebasthirani, K.

    ISSN: 1687-8132, 1687-8140
    Published: London, England SAGE Publications 01.04.2025
    Published in Advances in mechanical engineering (01.04.2025)
    “…) controllers, leveraging Genetic Algorithm (GA) and Hybrid Reinforcement Genetic Algorithm-Recursive Backpropagation Learning (GA-RBL…”
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    Journal Article
  3. 3

    Mechanical Property Prediction of Wood Using a Backpropagation Neural Network Optimized by Adaptive Fractional-Order Particle Swarm Algorithm by Huang, Jiahui, Kuang, Zhufang

    ISSN: 1999-4907, 1999-4907
    Published: Basel MDPI AG 01.08.2025
    Published in Forests (01.08.2025)
    “…) with adaptive fractional-order particle swarm optimization (AFPSO) and Liang–Kleeman (LK) information flow theory…”
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    Journal Article
  4. 4

    Fractional-order gradient descent learning of BP neural networks with Caputo derivative by Wang, Jian, Wen, Yanqing, Gou, Yida, Ye, Zhenyun, Chen, Hua

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Published: United States Elsevier Ltd 01.05.2017
    Published in Neural networks (01.05.2017)
    “… The monotonicity and weak (strong) convergence of the proposed approach are proved in detail. Two simulations have been implemented to illustrate the performance of presented fractional-order BP algorithm on three small datasets and one large dataset…”
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    Journal Article
  5. 5

    Convergence Analysis of Novel Fractional-Order Backpropagation Neural Networks With Regularization Terms by Ma, Mingjie, Yang, Jianhui

    ISSN: 2168-2267, 2168-2275, 2168-2275
    Published: United States IEEE 01.05.2024
    Published in IEEE transactions on cybernetics (01.05.2024)
    “…Fractional-order derivatives have the potential to improve the performance of backpropagation (BP) neural networks…”
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    Journal Article
  6. 6

    Physics-Informed Fractional-Order Recurrent Neural Network for Fast Battery Degradation with Vehicle Charging Snippets by Wang, Yanan, Wei, Min, Dai, Feng, Zou, Daijiang, Lu, Chen, Han, Xuebing, Chen, Yangquan, Ji, Changwei

    ISSN: 2504-3110, 2504-3110
    Published: Basel MDPI AG 01.02.2025
    Published in Fractal and fractional (01.02.2025)
    “… In this paper, we propose a physics-informed recurrent neural network (PIRNN) with a fractional-order gradient for fast…”
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    Journal Article
  7. 7

    Physics-Informed Recurrent Neural Network With Fractional-Order Gradients for State-of-Charge Estimation of Lithium-Ion Battery by Wang, Yanan, Han, Xuebing, Guo, Dongxu, Lu, Languang, Chen, Yangquan, Ouyang, Minggao

    ISSN: 2469-7281, 2469-729X
    Published: Piscataway IEEE 2022
    “… This paper introduces fractional-order gradients for RNN to improve its backpropagation process, so that network updates weights instructed by the fractional-order characteristics of LIB…”
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    Journal Article
  8. 8

    Fractional-order gradient approach for optimizing neural networks: A theoretical and empirical analysis by Harjule, Priyanka, Sharma, Rinki, Kumar, Rajesh

    ISSN: 0960-0779
    Published: Elsevier Ltd 01.03.2025
    Published in Chaos, solitons and fractals (01.03.2025)
    “…This article proposes a modified fractional gradient descent algorithm to enhance the learning capabilities of neural networks, comprising the benefits of a metaheuristic optimizer…”
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    Journal Article
  9. 9

    Sensitivity of Fractional-Order Recurrent Neural Network with Encoded Physics-Informed Battery Knowledge by Wang, Yanan, Han, Xuebing, Lu, Languang, Chen, Yangquan, Ouyang, Minggao

    ISSN: 2504-3110, 2504-3110
    Published: Basel MDPI AG 01.11.2022
    Published in Fractal and fractional (01.11.2022)
    “… For LIB state estimation, this work proposes a fractional-order recurrent neural network (FORNN…”
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    Journal Article
  10. 10

    Comparative study of integer-order and fractional-order artificial neural networks: Application for mathematical function generation by Joshi, Manisha Premkumar, Bhosale, Savita, Vyawahare, Vishwesh A.

    ISSN: 2772-6711, 2772-6711
    Published: Elsevier Ltd 01.06.2024
    Published in e-Prime (01.06.2024)
    “…: Perceptron employs a fractional derivative of the activation function and the steepest gradient-based learning algorithm…”
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    Journal Article
  11. 11

    Improved fractional-order gradient descent method based on multilayer perceptron by Zhou, Xiaojun, Zhao, Chunna, Huang, Yaqun, Zhou, Chengli, Ye, Junjie

    ISSN: 0893-6080, 1879-2782, 1879-2782
    Published: United States Elsevier Ltd 01.03.2025
    Published in Neural networks (01.03.2025)
    “… Moreover, the implementation of FOGD in the hidden layers serves as a necessary foundation for establishing a family of fractional-order deep learning optimizers, facilitating the widespread…”
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    Journal Article
  12. 12

    Numerical Simulation and Computational Methods in Engineering and Sciences

    ISBN: 9783725809554, 3725809569, 3725809550, 9783725809561
    Published: MDPI - Multidisciplinary Digital Publishing Institute 2024
    “… This Special Issue compiles cutting-edge research on mathematical simulation and computational techniques, emphasizing innovative algorithms and their cross-field applications…”
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    eBook
  13. 13

    Fractional Order Backpropagation Neural Network for Battery Capacity Estimation with Realistic Vehicle Data by Wang, Yanan, Han, Xuebing, Dai, Feng, Li, Jie, Zou, Daijiang, Lu, Languang, Chen, Yangquan, Ouyang, Minggao

    Published: IEEE 28.11.2022
    “… On the basis of fractional-order calculus, this paper proposes a fractional-order backpropagation neural network (BPNN…”
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    Conference Proceeding
  14. 14

    Accurate prediction of protein–ATP binding sites based on a protein pretrained large language model and a fractional-order convolutional neural network by Guo, Mengyao, Tu, Yuhang, Yu, Jiali, Wang, Yishu

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 25.11.2025
    Published in Scientific reports (25.11.2025)
    “… However, current research methods face numerous challenges, such as the need for various algorithms to extract multilevel features and then integrate them into one deep learning model…”
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    Journal Article
  15. 15

    Estimation of chlorophyll content of Cinnamomum camphora leaves based on hyperspectral and fractional order differentiation by Yang, Baocheng, Zhang, Haina, Lu, Xianghui, Zhang, Yue, Wan, Haolong, Luo, Xin, Zhang, Jie

    ISSN: 0143-1161, 1366-5901, 1366-5901
    Published: London Taylor & Francis 02.08.2024
    Published in International journal of remote sensing (02.08.2024)
    “…Hyperspectral remote sensing combined with data preprocessing techniques and machine learning algorithms is a new way to efficiently estimate plant SPAD…”
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    Journal Article
  16. 16

    Fractional-order differential evolution for training dendritic neuron model by Su, Kunqi, Jin, Ting, Gao, Jinrui

    ISSN: 1573-0484, 0920-8542, 1573-0484
    Published: New York Springer Nature B.V 08.11.2025
    Published in The Journal of supercomputing (08.11.2025)
    “… and the differential evolution algorithm to train DNM, referred to as fractional-order differential evolution (FODE) algorithm…”
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    Journal Article
  17. 17

    Design of an Online Adaptive FractionalOrder Proportional‐Integral‐Derivative Controller to Reduce the Seismic Response of the 20‐Story Benchmark Building Equipped with an Active Control System by Jafarzadeh, Ommegolsoum, Mousavi Ghasemi, Seyyed Arash, Zahrai, Seyed Mehdi, Sabetahd, Rasoul, Mohammadzadeh, Ardashir, Vafaei Poursorkhabi, Ramin

    ISSN: 0884-8173, 1098-111X
    Published: New York John Wiley & Sons, Inc 2024
    “… Utilizing the backpropagation algorithm in training a multilayer perceptron neural network is deemed effective in identifying the structural system and estimating the plant…”
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    Journal Article
  18. 18

    Inversion of Water Quality Parameters from UAV Hyperspectral Data Based on Intelligent Algorithm Optimized Backpropagation Neural Networks of a Small Rural River by Wang, Manqi, Zhou, Caili, Shi, Jiaqi, Lin, Fei, Li, Yucheng, Hu, Yimin, Zhang, Xuesheng

    ISSN: 2072-4292, 2072-4292
    Published: Basel MDPI AG 01.01.2025
    Published in Remote sensing (Basel, Switzerland) (01.01.2025)
    “… Firstly, the spectral data were preprocessed using fractional order derivation (FOD), standard normal variate (SNV…”
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    Journal Article
  19. 19

    Design of stochastic backpropagative autoregressive exogenous neuroarchitectures for predictive analysis of fractional-order nonlinear Rabinovich–Fabrikant chaotic attractors by Hassan, Shahzaib Ahmed, Raja, Muhammad Junaid Ali Asif, Sherazi, Syed Zoraiz Ali, Chang, Chuan-Yu, Shu, Chi-Min, Kiani, Adiqa Kausar, Khan, Zeshan Aslam, Shoaib, Muhammad, Raja, Muhammad Asif Zahoor

    ISSN: 0924-090X, 1573-269X
    Published: Dordrecht Springer Nature B.V 01.12.2025
    Published in Nonlinear dynamics (01.12.2025)
    “… sensitive dependence on initial conditions within multifaceted physical contexts. In this paper, we present a fractional-order Rabinovich–Fabrikant (FO–RF…”
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    Journal Article
  20. 20

    Physics-Informed Recurrent Neural Networks with Fractional-Order Constraints for the State Estimation of Lithium-Ion Batteries by Wang, Yanan, Han, Xuebing, Guo, Dongxu, Lu, Languang, Chen, Yangquan, Ouyang, Minggao

    ISSN: 2313-0105, 2313-0105
    Published: Basel MDPI AG 01.10.2022
    Published in Batteries (Basel) (01.10.2022)
    “… Rather than using complex partial differential equations and the complicated parameter tuning of a model-based method, a machine learning algorithm provides a new paradigm and has been…”
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    Journal Article