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  • Open Access

    ARTICLE

    Adaptive Sliding Mode Control Method for Onboard Supercapacitors System

    Yanzan Han1,*, Hang Zhou1, Zengfang Shi1, Shuang Liang2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1099-1108, 2022, DOI:10.32604/csse.2022.017741 - 24 September 2021

    Abstract Urban rail trains have undergone rapid development in recent years due to their punctuality, high capacity and energy efficiency. Urban trains require frequent start/stop operations and are, therefore, prone to high energy losses. As trains have high inertia, the energy that can be recovered from braking comes in short bursts of high power. To effectively recover such braking energy, an onboard supercapacitor system based on a radial basis function neural network-based sliding mode control system is proposed, which provides robust adaptive performance. The supercapacitor energy storage system is connected to a bidirectional DC/DC converter to More >

  • Open Access

    ARTICLE

    Three Dimensional Optimum Node Localization in Dynamic Wireless Sensor Networks

    Gagandeep Singh Walia1, Parulpreet Singh1, Manwinder Singh1, Mohamed Abouhawwash2,3, Hyung Ju Park4, Byeong-Gwon Kang4,*, Shubham Mahajan5, Amit Kant Pandit5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 305-321, 2022, DOI:10.32604/cmc.2022.019171 - 07 September 2021

    Abstract Location information plays an important role in most of the applications in Wireless Sensor Network (WSN). Recently, many localization techniques have been proposed, while most of these deals with two Dimensional applications. Whereas, in Three Dimensional applications the task is complex and there are large variations in the altitude levels. In these 3D environments, the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level. For such applications, 2D localization models are not reliable. Due to this, the design of 3D localization systems in WSNs faces new challenges. In this… More >

  • Open Access

    ARTICLE

    A New Fuzzy Adaptive Algorithm to Classify Imbalanced Data

    Harshita Patel1, Dharmendra Singh Rajput1,*, Ovidiu Petru Stan2, Liviu Cristian Miclea2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 73-89, 2022, DOI:10.32604/cmc.2022.017114 - 07 September 2021

    Abstract Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other classes. The Imbalanced distribution of data is a natural occurrence in real world datasets, so needed to be dealt with carefully to get important insights. In case of imbalance in data sets, traditional classifiers have to sacrifice their performances, therefore lead to misclassifications. This paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this issue. We have adapted the ‘existing algorithm modification solution’ to learn… More >

  • Open Access

    ARTICLE

    Tour Planning Design for Mobile Robots Using Pruned Adaptive Resonance Theory Networks

    S. Palani Murugan1,*, M. Chinnadurai1, S. Manikandan2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 181-194, 2022, DOI:10.32604/cmc.2022.016152 - 07 September 2021

    Abstract The development of intelligent algorithms for controlling autonom- ous mobile robots in real-time activities has increased dramatically in recent years. However, conventional intelligent algorithms currently fail to accurately predict unexpected obstacles involved in tour paths and thereby suffer from inefficient tour trajectories. The present study addresses these issues by proposing a potential field integrated pruned adaptive resonance theory (PPART) neural network for effectively managing the touring process of autonomous mobile robots in real-time. The proposed system is implemented using the AlphaBot platform, and the performance of the system is evaluated according to the obstacle prediction More >

  • Open Access

    ARTICLE

    An Efficient HAPS Cross-Layer Design to Mitigate COVID-19 Consequences

    Sameer Alsharif*, Rashid A. Saeed, Yasser Albagory

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 43-59, 2022, DOI:10.32604/iasc.2022.019493 - 03 September 2021

    Abstract This paper proposes a new cross-layer communication system for the provision of Internet services and applications to mitigate the negative impacts of COVID-19, due to which the massive online demands are affecting the current communication systems’ infrastructures and capabilities. The system requirements and model are investigated where it utilizes high-altitude platform (HAP) for fast and efficient connectivity provision to bridge the communication infrastructure gap in the current pandemic. The HAP is linked to the main server or gateway station located on ground and can provide communication narrow beams towards isolated areas which suffer from poor… More >

  • Open Access

    ARTICLE

    A Dynamic Adaptive Firefly Algorithm for Flexible Job Shop Scheduling

    K. Gayathri Devi*, R. S. Mishra, A. K. Madan

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 429-448, 2022, DOI:10.32604/iasc.2022.019330 - 03 September 2021

    Abstract An NP-hard problem like Flexible Job Shop Scheduling (FJSP) tends to be more complex and requires more computational effort to optimize the objectives with contradictory measures. This paper aims to address the FJSP problem with combined and contradictory objectives, like minimization of make-span, maximum workload, and total workload. This paper proposes ‘Hybrid Adaptive Firefly Algorithm’ (HAdFA), a new enhanced version of the classic Firefly Algorithm (FA) embedded with adaptive parameters to optimize the multi objectives concurrently. The proposed algorithm has adopted two adaptive strategies, i.e., an adaptive randomization parameter (α) and an effective heterogeneous update More >

  • Open Access

    ARTICLE

    Energy Saving Control Approach for Trajectory Tracking of Autonomous Mobile Robots

    Yung-Hsiang Chen1, Yung-Yue Chen2, Shi-Jer Lou3, Chiou-Jye Huang4,*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 357-372, 2022, DOI:10.32604/iasc.2022.018663 - 03 September 2021

    Abstract This research presents an adaptive energy-saving H2 closed-form control approach to solve the nonlinear trajectory tracking problem of autonomous mobile robots (AMRs). The main contributions of this proposed design are as follows: closed-form approach, simple structure of the control law, easy implementation, and energy savings through trajectory tracking design of the controlled AMRs. It is difficult to mathematically obtained this adaptive H2 closed-form solution of AMRs. Therefore, through a series of mathematical analyses of the trajectory tracking error dynamics of the controlled AMRs, the trajectory tracking problem of AMRs can be transformed directly into a solvable More >

  • Open Access

    ARTICLE

    Quantum Steganography Application in the Electrical Network for Quantum Image and Watermark with Self-Adaptive

    Jie Shen1,3,*,#, Wenqi Dong2,#, Jing Wang1,2,3,#, Yang Wang1, Haiyan Li4

    Journal of Information Hiding and Privacy Protection, Vol.3, No.3, pp. 109-120, 2021, DOI:10.32604/jihpp.2021.025602 - 07 February 2022

    Abstract With the development of Globe Energy Internet, quantum steganography has been used for information hiding to improve copyright protection. Based on secure quantum communication protocol, and flexible steganography, secret information is embedded in quantum images in covert communication. Under the premise of guaranteeing the quality of the quantum image, the secret information is transmitted safely with virtue of good imperceptibility. A novel quantum watermark algorithm is proposed in the paper, based on the shared group key value of the communication parties and the transmission of the selected carrier map pixel gray higher than 8 bits. More >

  • Open Access

    ARTICLE

    Ground Nephogram Enhancement Algorithm Based on Improved Adaptive Fractional Differentiation

    Xiaoying Chen1,*, Jie Kang1, Cong Hu2

    Journal of New Media, Vol.3, No.4, pp. 151-180, 2021, DOI:10.32604/jnm.2021.024665 - 05 November 2021

    Abstract The texture of ground-based nephogram is abundant and multiplicity. Many cloud textures are not as clear as artificial textures. A nephogram enhancement algorithm based on Adaptive Fractional Differential is established to extract the natural texture of visible ground-based cloud image. GrunwaldLentikov (G-L) and Grunwald-Lentikov (R-L) fractional differential operators are applied to the enhancement algorithm of ground-based nephogram. An operator mask based on adaptive differential order is designed. The corresponding mask template is used to process each pixel. The results show that this method can extract image texture and edge details and simplify the process of More >

  • Open Access

    ARTICLE

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

    Dequan Guo1, Qingshuai Yang2, Yu-Dong Zhang3, Gexiang Zhang1, Ming Zhu1, Jianying Yuan1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 191-205, 2021, DOI:10.32604/cmes.2021.016347 - 24 August 2021

    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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