仿真建模作为设计和开发大型自动化系统的工具——在缺乏统计信息的情况下应用智能城市

D. Razumov, V. Aleshin
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引用次数: 0

摘要

大型自动化系统(AS)的设计和开发总是与克服大量的不确定性相关,这些不确定性通常通过使用系统和软件工程中的实践标准和建模来构建。大型系统(LS)的分析方法包括在结构和/或功能范式的背景下对其进行分解,这允许我们将获得的组件视为建模的对象:功能建模,仿真等。设计区域(智慧城市项目)需要优化决策的自动化控制系统(ACS)。本文在仿真模型的基础上,提出了在缺乏统计信息的情况下确定工程参数的新方法。
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A Simulation Modelling as a Tool for Design and Development Large-Scale Automated Systems Smart City Application in Terms of Lack Statistical Information
Design and development of large-scale automated systems (AS) is always associated with overcoming a large number of uncertainties, which structuring often through the using of practice standards and modeling at the Systems & Software Engineering. Methods of analysis of large systems (LS) involve their decomposition in the context of structural and/or functional paradigms, which allow us to consider the obtained components as objects for modelling: functional modelling, simulation etc. Design the automated control system (ACS) of region (SmartCity project) need to optimize the decisions. In this paper we propose the new methods of determining the parameters of project in terms of lack statistical information based on the simulation model.
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Advances in Systems Science and Applications
Advances in Systems Science and Applications Engineering-Engineering (all)
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1.20
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期刊介绍: Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.
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