利用卡普托导数在无线传感器网络中传输恶意代码的人工神经网络方法

IF 1.6 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Zia Ullah Khan, Mati ur Rahman, Muhammad Arfan,  Waseem, Salah Boulaaras
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引用次数: 0

摘要

本手稿研究了无线传感器网络中恶意代码的六个分区数学模型,并考虑了卡普托分式算子及其数值方案。网络传感器的六个代理节点可以像感染一样在不同节点的社区中转移。在定点理论的帮助下,还给出了上述模型解的存在性和唯一性。在分数格式下的数值求解方案是根据分数阶数的选择制定的,这增加了此类网络分析的自由度。给出了所有六个代理在不同分数阶数下的数值模拟,以及分数阶数和一些使用参数的敏感性。新的人工神经网络(ANN)分析方法已用于所考虑的模型,并与亚当斯-巴什福斯(AB)方法进行了比较。我们使用 ANN 方法将数据集分为训练、测试和验证三类,并在本作品中进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The artificial neural network approach for the transmission of malicious codes in wireless sensor networks with Caputo derivative

The current manuscript investigates a six compartmental mathematical model for malicious Codes in Wireless Sensor Network is consider for investigation under the fractional operator of Caputo along with their numerical scheme. The six agent nodes of the network sensors are transferable like in infection with in their community of different nodes. With the help of fixed point theory the presentation of existence and uniqueness of solution of the said model are also given. The scheme of numerical solution under fractional format is developed with the choice of fractional orders which increasing the degree of freedom for such type of network analysis. The numerical simulation of all the six agents are given on different fractional orders along with sensitivity of the fractional orders and some used parameters. The new analysis artificial neural network (ANN) method has been utilized for the considered model and compared with Adams–Bashforth (AB) method. We divided the data set into three categories training, testing and validation with ANN method and the analysis is presented in this work.

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来源期刊
CiteScore
4.60
自引率
6.20%
发文量
101
审稿时长
>12 weeks
期刊介绍: Prediction through modelling forms the basis of engineering design. The computational power at the fingertips of the professional engineer is increasing enormously and techniques for computer simulation are changing rapidly. Engineers need models which relate to their design area and which are adaptable to new design concepts. They also need efficient and friendly ways of presenting, viewing and transmitting the data associated with their models. The International Journal of Numerical Modelling: Electronic Networks, Devices and Fields provides a communication vehicle for numerical modelling methods and data preparation methods associated with electrical and electronic circuits and fields. It concentrates on numerical modelling rather than abstract numerical mathematics. Contributions on numerical modelling will cover the entire subject of electrical and electronic engineering. They will range from electrical distribution networks to integrated circuits on VLSI design, and from static electric and magnetic fields through microwaves to optical design. They will also include the use of electrical networks as a modelling medium.
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