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  1. 701
  2. 702

    Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification by Mhd Saeed Sharif, Maysam Abbod, Abbes Amira, Habib Zaidi

    Published 2012-01-01
    “…The first methodology is a competitive neural network (CNN), whereas the second one is based on learning vector quantisation neural network (LVQNN). …”
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    Article
  3. 703

    Research on blow-out of shield tunnel in sandy soil with shallow burial by Yong-Xiang Shi, Yong-Xiang Shi, Bao-Ping Xi, Qi-Guang Di, Feng-Nian Wang, Feng-Nian Wang

    Published 2025-01-01
    “…The research study the effects of burial depth to diameter ratio and the angle of internal friction on the ultimate support pressure and the shape of the failure zone. …”
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    Article
  4. 704

    Performance Evaluation of Laboratory Management System Based on BP Neural Network by Anjie Su, Zhigang Wu, Yifeng Yin

    Published 2022-01-01
    “…Based on the exploration of neural network, this paper combines BP neural network with performance evaluation and applies BP neural network to the performance evaluation of university laboratories. …”
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    Article
  5. 705

    State Estimation for Discrete-Time Stochastic Neural Networks with Mixed Delays by Liyuan Hou, Hong Zhu, Shouming Zhong, Yong Zeng, Lin Shi

    Published 2014-01-01
    “…This paper investigates the analysis problem for stability of discrete-time neural networks (NNs) with discrete- and distribute-time delay. …”
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  6. 706

    Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays by Weisong Zhou, Zhichun Yang

    Published 2012-01-01
    “…A class of dynamical neural network models with time-varying delays is considered. …”
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    Article
  7. 707
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    Fixed-Time Synchronization of Delayed Memristive Neural Networks with Discontinuous Activations by Hao Pu, Fengjun Li

    Published 2021-01-01
    “…In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated. …”
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    Article
  9. 709

    Analysis of Influence Law of Burial Depth on Surrounding Rock Deformation of Roadway by Hai Wu, Xiaokang Wang, Weijian Yu, Weijun Wang, Zizheng Zhang, Gang Peng

    Published 2020-01-01
    “…In order to study the influence of burial depth on the roadway deformation, the deformation data of more than 100 roadways were collected and classified. …”
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  10. 710

    Dynamical Behaviors of the Stochastic Hopfield Neural Networks with Mixed Time Delays by Li Wan, Qinghua Zhou, Zhigang Zhou, Pei Wang

    Published 2013-01-01
    “…This paper investigates dynamical behaviors of the stochastic Hopfield neural networks with mixed time delays. The mixed time delays under consideration comprise both the discrete time-varying delays and the distributed time-delays. …”
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    Incisor Malocclusion Using Cut-out Method and Convolutional Neural Network by Muhamad Farhin Harun, Azurah A Samah, Muhammmad Imran Ahmad Shabuli, Hairudin Abdul Majid, Haslina Hashim, Nor Azman Ismail, Syiral Mastura Abdullah, Aspalilah Alias

    Published 2022-10-01
    “…This study has developed a malocclusion classification model using the cut-out method and Convolutional Neural Network (CNN). The cut-out method restructures the input images by standardising the sizes and highlighting the incisor sections of the images which assisted the CNN in accurately classifying the malocclusion. …”
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  15. 715
  16. 716

    Tourism Demand Forecasting Based on Grey Model and BP Neural Network by Xing Ma

    Published 2021-01-01
    “…Then, combining BP neural network with the grey model, the grey neural network combination model is established to forecast the number of tourists. …”
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    Nonlinear Time-Delay Suspension Adaptive Neural Network Active Control by Yue Zhu, Sihong Zhu

    Published 2014-01-01
    “…By recognizing and training the adaptive neural network, the adaptive neural network active suspension controller is obtained. …”
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  20. 720

    Analysis of Consumer Behavior Data Based on Deep Neural Network Model by Shijiao Yuan

    Published 2022-01-01
    “…In this algorithm, the sheep nodes are not fixed, but the number of hidden layers and unit nodes of the neural network are dynamically determined according to the sample training. …”
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