AI-Assisted Dynamic Modelling for Data Management in a Distributed System

IF 0.9 Q4 MANAGEMENT
Yingjun Wang, Shaoyang He, Yiran Wang
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引用次数: 0

Abstract

There are many interdependent computers available in distributed networks. In such schemes, overall ownership costs comprise facilities, such as computers, controls, etc.; buying hardware; and running expenses such as wages, electrical charges, etc. Strom use is a large part of operating expenses. AI-assisted dynamic modelling for data management (AI-DM) framework is proposed. The high percentage of power use is connected explicitly to inadequate planning of energy. This research suggests creating a multi-objective method to plan the preparation of multi-criteria software solutions for distributed systems using the fuzzy TOPSIS tool as a comprehensive guide to multi-criteria management. The execution results demonstrate that this strategy could then sacrifice requirements by weight.
分布式系统中数据管理的人工智能辅助动态建模
分布式网络中有许多相互依赖的计算机。在这种方案中,总体拥有成本包括设施,如计算机、控制等;购买硬件;以及工资、电费等运营费用。Strom的使用是运营费用的很大一部分。提出了人工智能辅助数据管理动态建模(AI-DM)框架。高比例的电力使用明显与能源规划不充分有关。本研究建议创建一种多目标方法,利用模糊TOPSIS工具为分布式系统规划多标准软件解决方案的准备工作,作为多标准管理的综合指南。执行结果表明,该策略可以通过权重来牺牲需求。
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来源期刊
CiteScore
1.90
自引率
43.80%
发文量
59
期刊介绍: The International Journal of Information Systems and Supply Chain Management (IJISSCM) provides a practical and comprehensive forum for exchanging novel research ideas or down-to-earth practices which bridge the latest information technology and supply chain management. IJISSCM encourages submissions on how various information systems improve supply chain management, as well as how the advancement of supply chain management tools affects the information systems growth. The aim of this journal is to bring together the expertise of people who have worked with supply chain management across the world for people in the field of information systems.
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