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  • Open Access

    ARTICLE

    An Industrial Intrusion Detection Method Based on Hybrid Convolutional Neural Networks with Improved TCN

    Zhihua Liu, Shengquan Liu*, Jian Zhang

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 411-433, 2024, DOI:10.32604/cmc.2023.046237

    Abstract Network intrusion detection systems (NIDS) based on deep learning have continued to make significant advances. However, the following challenges remain: on the one hand, simply applying only Temporal Convolutional Networks (TCNs) can lead to models that ignore the impact of network traffic features at different scales on the detection performance. On the other hand, some intrusion detection methods consider multi-scale information of traffic data, but considering only forward network traffic information can lead to deficiencies in capturing multi-scale temporal features. To address both of these issues, we propose a hybrid Convolutional Neural Network that supports a multi-output strategy (BONUS) for… More >

  • Open Access

    ARTICLE

    Fuzzy Hybrid Coyote Optimization Algorithm for Image Thresholding

    Linguo Li1,2, Xuwen Huang2, Shunqiang Qian2, Zhangfei Li2, Shujing Li2,*, Romany F. Mansour3

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3073-3090, 2022, DOI:10.32604/cmc.2022.026625

    Abstract In order to address the problems of Coyote Optimization Algorithm in image thresholding, such as easily falling into local optimum, and slow convergence speed, a Fuzzy Hybrid Coyote Optimization Algorithm (hereinafter referred to as FHCOA) based on chaotic initialization and reverse learning strategy is proposed, and its effect on image thresholding is verified. Through chaotic initialization, the random number initialization mode in the standard coyote optimization algorithm (COA) is replaced by chaotic sequence. Such sequence is nonlinear and long-term unpredictable, these characteristics can effectively improve the diversity of the population in the optimization algorithm. Therefore, in this paper we first… More >

  • Open Access

    ARTICLE

    A Negotiated Pricing Model for Innovation Services Based on the Multiobjective Genetic Algorithm

    Yan Zhou1,*, Yue Li1, Yunxing Zhang2

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 191-203, 2021, DOI:10.32604/iasc.2021.014142

    Abstract Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern to the suppliers and demanders. In this paper, a negotiated pricing model that is based on the multiobjective genetic algorithm is developed for innovation services. Regarding the process of service pricing as a multiobjective problem, the objective functions which include the service price, service efficiency, and service quality for the suppliers and the demanders are constructed. Because the solution of a multiobjective problem is typically a series of alternatives, an additional negotiation process is necessary in determining the final decision. A… More >

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