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Modeling and Analysis of Autonomous Intelligence

Submission Deadline: 31 December 2021 (closed) View: 875 Submit to Journal

Guest Editors

Prof. Shiping Wen, University of Technology Sydney, Australia
Prof. Yin Yang, Hamad Bin Khalifa University, Qatar

Summary

For intelligent control, the implication is that, without a similar brain-body-environment triumvirate, self-driving cars, drones and agile robots will be forever limited to environments they have been programmed to navigate. Currently, progress in autonomy for these artificial agents is constrained by the available learning algorithms and design methods, most of which only work in static environments. As a result, they exhibit crippling fragility in unstructured and changing environments. Therefore, this topic aims to promote the development of autonomous control methods to be adapted to dynamically changing tasks and environments in real-time. Therefore, this topic is suitable for a special issue of CMES.

Keywords

• Autonomous intelligence
• Model design of general deep networks
• Neurodynamical analysis and application
• Dynamic analysis of deep neural networks
• Efficient training analysis for deep learning
• Deep neural network based control method
• Deep neural networks for image processing
• Robotic system modeling and its application
• Mathematical analysis of deep neural networks
• New meta-heuristic algorithm and its application
• Deep neural network based algorithms in smart grids
• New model of memristor-based system and its application
• Novel deep network architecture for emerging nano-devices
• Plug-in Electric Vehicle (PEV) management via learning systems
• The other related topics

Published Papers

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  • Open Access

    ARTICLE

    Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with Discontinuous Activations

    Tianyuan Jia, Xiangyong Chen, Xiurong Yao, Feng Zhao, Jianlong Qiu
    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 221-239, 2023, DOI:10.32604/cmes.2022.020780
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract Fixed-time synchronization (FTS) of delayed memristor-based neural networks (MNNs) with discontinuous activations is studied in this paper. Both continuous and discontinuous activations are considered for MNNs. And the mixed delays which are closer to reality are taken into the system. Besides, two kinds of control schemes are proposed, including feedback and adaptive control strategies. Based on some lemmas, mathematical inequalities and the designed controllers, a few synchronization criteria are acquired. Moreover, the upper bound of settling time (ST) which is independent of the initial values is given. Finally, the feasibility of our theory is attested More >

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  • Open Access

    ARTICLE

    Fixed-Time Adaptive Time-Varying Matrix Projective Synchronization of Time-Delayed Chaotic Systems with Different Dimensions

    Peng Zheng, Xiaozhen Guo, Guoguang Wen
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1451-1463, 2022, DOI:10.32604/cmes.2022.019769
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract This paper deals with the fixed-time adaptive time-varying matrix projective synchronization (ATVMPS) of different dimensional chaotic systems (DDCSs) with time delays and unknown parameters. Firstly, to estimate the unknown parameters, adaptive parameter updated laws are designed. Secondly, to realize the fixed-time ATVMPS of the time-delayed DDCSs, an adaptive delay-unrelated controller is designed, where time delays of chaotic systems are known or unknown. Thirdly, some simple fixed-time ATVMPS criteria are deduced, and the rigorous proof is provided by employing the inequality technique and Lyapunov theory. Furthermore, the settling time of fixed-time synchronization (Fix-TS) is obtained, which More >

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    2089

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    1164

  • Open Access

    ARTICLE

    A Map Construction Method Based on the Cognitive Mechanism of Rat Brain Hippocampus

    Naigong Yu, Hejie Yu
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1147-1169, 2022, DOI:10.32604/cmes.2022.019430
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract The entorhinal-hippocampus structure in the mammalian brain is the core area for realizing spatial cognition. However, the visual perception and loop detection methods in the current biomimetic robot navigation model still rely on traditional visual SLAM schemes and lack the process of exploring and applying biological visual methods. Based on this, we propose a map construction method that mimics the entorhinal-hippocampal cognitive mechanism of the rat brain according to the response of entorhinal cortex neurons to eye saccades in recent related studies. That is, when mammals are free to watch the scene, the entorhinal cortex… More >

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    2561

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    1414

  • Open Access

    ARTICLE

    Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene

    Zhen Xu, Shuai Guo, Tao Song, Yuwen Li, Lingdong Zeng
    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1853-1882, 2022, DOI:10.32604/cmes.2022.018004
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability. Localization of mobile robot is increasingly important for the printing of buildings in the construction scene. Although many available studies on the localization have been conducted, only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes. To realize the accurate localization of mobile robot in designated stations, we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of More >

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    2635

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    1784

  • Open Access

    ARTICLE

    Action Recognition Based on CSI Signal Using Improved Deep Residual Network Model

    Jian Zhao, Shangwu Chong, Liang Huang, Xin Li, Chen He, Jian Jia
    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1827-1851, 2022, DOI:10.32604/cmes.2022.017654
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract In this paper, we propose an improved deep residual network model to recognize human actions. Action data is composed of channel state information signals, which are continuous fine-grained signals. We replaced the traditional identity connection with the shrinking threshold module. The module automatically adjusts the threshold of the action data signal, and filters out signals that are not related to the principal components. We use the attention mechanism to improve the memory of the network model to the action signal, so as to better recognize the action. To verify the validity of the experiment more More >

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    2445

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    1641

  • Open Access

    ARTICLE

    Traffic Flow Statistics Method Based on Deep Learning and Multi-Feature Fusion

    Liang Mu, Hong Zhao, Yan Li, Xiaotong Liu, Junzheng Qiu, Chuanlong Sun
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 465-483, 2021, DOI:10.32604/cmes.2021.017276
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract Traffic flow statistics have become a particularly important part of intelligent transportation. To solve the problems of low real-time robustness and accuracy in traffic flow statistics. In the DeepSort tracking algorithm, the Kalman filter (KF), which is only suitable for linear problems, is replaced by the extended Kalman filter (EKF), which can effectively solve nonlinear problems and integrate the Histogram of Oriented Gradient (HOG) of the target. The multi-target tracking framework was constructed with YOLO V5 target detection algorithm. An efficient and long-running Traffic Flow Statistical framework (TFSF) is established based on the tracking framework.… More >

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    3633

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    2354

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    1

  • Open Access

    ARTICLE

    Adaptive Object Tracking Discriminate Model for Multi-Camera Panorama Surveillance in Airport Apron

    Dequan Guo, Qingshuai Yang, Yu-Dong Zhang, Gexiang Zhang, Ming Zhu, Jianying Yuan
    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 191-205, 2021, DOI:10.32604/cmes.2021.016347
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract Autonomous intelligence plays a significant role in aviation security. Since most aviation accidents occur in the take-off and landing stage, accurate tracking of moving object in airport apron will be a vital approach to ensure the operation of the aircraft safely. In this study, an adaptive object tracking method based on a discriminant is proposed in multi-camera panorama surveillance of large-scale airport apron. Firstly, based on channels of color histogram, the pre-estimated object probability map is employed to reduce searching computation, and the optimization of the disturbance suppression options can make good resistance to similar More >

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    2994

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    1841

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    1

  • Open Access

    ARTICLE

    Method for Collision Avoidance in Spacecraft Rendezvous Problems with Space Objects in a Phasing Orbit

    Danhe Chen, A. A. Baranov, Chuangge Wang, M. O. Karatunov, N. Yu. Makarov
    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 977-991, 2021, DOI:10.32604/cmes.2021.014662
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract As the number of space objects (SO) increases, collision avoidance problem in the rendezvous tasks or re-constellation of satellites with SO has been paid more attention, and the dangerous area of a possible collision should be derived. In this paper, a maneuvering method is proposed for avoiding collision with a space debris object in the phasing orbit of the initial optimal solution. Accordingly, based on the plane of eccentricity vector components, relevant dangerous area which is bounded by two parallel lines is formulated. The axises of eccentricity vector system pass through the end of eccentricity… More >

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    3696

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    2435

  • Open Access

    ARTICLE

    Remote Sensing Monitoring Method Based on BDS-Based Maritime Joint Positioning Model

    Xiang Wang, Jingxian Liu, Osamah Ibrahim Khalaf, Zhao Liu
    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 801-818, 2021, DOI:10.32604/cmes.2021.013568
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract Complicated sea conditions have a serious impact on ship navigation safety and even maritime accidents. Accordingly, this paper proposes a remote sensing monitoring method based on the Beidou Navigation Satellite System (BDS) maritime joint positioning model. This method is mainly based on the BDS and multiple Global Navigation Satellite Systems (GNSS) to build a data fusion model, which can capture more steady positioning, navigation, and timing (PNT) data. Compared with the current Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) mandatory used by the International Maritime Organization (IMO), this model has the characteristics More >

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    3269

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    2174

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    1

    Cited by

    7

  • Open Access

    ARTICLE

    Improvement of Orbit Prediction Algorithm for Spacecraft Through Simplified Precession-Nutation Model Using Cubic Spline Interpolation Method

    Gen Xu, Danhe Chen, Xiang Zhang, Wenhe Liao
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 865-878, 2020, DOI:10.32604/cmes.2020.012844
    （This article belongs to the Special Issue: Modeling and Analysis of Autonomous Intelligence)
    Abstract For the on-orbit flight missions, the model of orbit prediction is critical for the tasks with high accuracy requirement and limited computing resources of spacecraft. The precession-nutation model, as the main part of extended orbit prediction, affects the efficiency and accuracy of on-board operation. In this paper, the previous research about the conversion between the Geocentric Celestial Reference System and International Terrestrial Reference System is briefly summarized, and a practical concise precession-nutation model is proposed for coordinate transformation computation based on Celestial Intermediate Pole (CIP). The idea that simplifying the CIP-based model with interpolation method… More >

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    3280

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    2397

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    1

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