智能自动化系统设备储备优化

V. Chubaievskyi, V. Lakhno, B. Akhmetov, O. Kryvoruchko, D. Kasatkin, A. Desiatko, Taras Litovchenko
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引用次数: 2

摘要

提出了一种神经网络分析算法,用于智能城市自动控制系统中决策支持系统(DSS)的备用设备组成选择。本文提出了一种模型、算法和软件,用于解决在技术故障和攻击者破坏性干扰的情况下,选择能够确保IACS不间断运行的CBE的优化问题。与已知计算方法的结果相比,所提出的解决方案有助于将确定IACS最佳CBE的成本降低15-17%。给出了计算实验的结果,研究了神经网络分析仪的输出对IACS的CBE功能效率的影响程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OPTIMIZATION OF EQUIPMENT RESERVE FOR INTELLECTUAL AUTOMATED SYSTEMS
Algorithms for a neural network analyzer involved in the decision support system (DSS) during the selection of the composition of backup equipment (CBE) for intelligent automated control systems Smart City are proposed. A model, algorithms and software have been developed for solving the optimization problem of choosing a CBE capable of ensuring the uninterrupted operation of the IACS both in conditions of technological failures and in conditions of destructive interference in the operation of the IACS by the attackers. The proposed solutions help to reduce the cost of determining the optimal CBE for IACS by 15–17% in comparison with the results of known calculation methods. The results of computational experiments to study the degree of influence of the outputs of the neural network analyzer on the efficiency of the functioning of the CBE for IACS are presented.
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