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  • Open Access

    ARTICLE

    A Power Data Anomaly Detection Model Based on Deep Learning with Adaptive Feature Fusion

    Xiu Liu, Liang Gu*, Xin Gong, Long An, Xurui Gao, Juying Wu

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4045-4061, 2024, DOI:10.32604/cmc.2024.048442

    Abstract With the popularisation of intelligent power, power devices have different shapes, numbers and specifications. This means that the power data has distributional variability, the model learning process cannot achieve sufficient extraction of data features, which seriously affects the accuracy and performance of anomaly detection. Therefore, this paper proposes a deep learning-based anomaly detection model for power data, which integrates a data alignment enhancement technique based on random sampling and an adaptive feature fusion method leveraging dimension reduction. Aiming at the distribution variability of power data, this paper developed a sliding window-based data adjustment method for… More >

  • Open Access

    ARTICLE

    Tensor Train Random Projection

    Yani Feng1, Kejun Tang2, Lianxing He3, Pingqiang Zhou1, Qifeng Liao1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1195-1218, 2023, DOI:10.32604/cmes.2022.021636

    Abstract This work proposes a Tensor Train Random Projection (TTRP) method for dimension reduction, where pairwise distances can be approximately preserved. Our TTRP is systematically constructed through a Tensor Train (TT) representation with TT-ranks equal to one. Based on the tensor train format, this random projection method can speed up the dimension reduction procedure for high-dimensional datasets and requires fewer storage costs with little loss in accuracy, compared with existing methods. We provide a theoretical analysis of the bias and the variance of TTRP, which shows that this approach is an expected isometric projection with bounded More >

  • Open Access

    ARTICLE

    Clustering Gene Expression Data Through Modified Agglomerative M-CURE Hierarchical Algorithm

    E. Kavitha1,*, R. Tamilarasan2, N. Poonguzhali3, M. K. Jayanthi Kannan4

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1027-141, 2022, DOI:10.32604/csse.2022.020634

    Abstract Gene expression refers to the process in which the gene information is used in the functional gene product synthesis. They basically encode the proteins which in turn dictate the functionality of the cell. The first step in gene expression study involves the clustering usage. This is due to the reason that biological networks are very complex and the genes volume increases the comprehending challenges along with the data interpretation which itself inhibit vagueness, noise and imprecision. For a biological system to function, the essential cellular molecules must interact with its surrounding including RNA, DNA, metabolites… More >

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