Business Resilience System Integrated Artificial Intelligence System

Bahman Zohuri, Masoud Moghaddam, Farhang Mossavar-Rahmani
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引用次数: 4

Abstract

By definition, “Business Resilience” is the ability for an organization to quickly adapt to an unexpected disruption(s) and prevent any ongoing workflow(s) to come to a halt and yet maintaining continuous business operations and safeguarding people, resources, assets, and overall barns equity. By the same talking, a Business Resilience System (BRS) is a combination of intelligent software and hardware combined in an integrated system. Such an integrated combination of Business Resilience System goes a step beyond Disaster Recovery (DR) by offering post-disaster strategies to avoid costly downtime, shore up vulnerability and maintain business operations in the face of additional, unexpected breaches of the daily operation of workflow in any enterprise or organization. With recent technical progress in Artificial Intelligence (AI) augmented with Machine Learning (ML) and Deep Learning sub-systems, they present an Artificial Intelligence System (AIS) and now integrating these two systems of BRS and AIS, one can offer the most intelligent system that an organization or an enterprise can own, in order to have the best possible solution in place to have the best possible technique of predication and consequently prevention and adverse events based on collective historical data within Deep Learning of Artificial Intelligence. In this paper we are present and introduce each of these systems i.e., BRS and AIS and how they can be beneficial to each other by their integration as a holistic system along with their sub-stems of Software, Hardware, Machine Learning and Deep Learning.
商业弹性系统集成人工智能系统
根据定义,“业务弹性”是组织快速适应意外中断并防止任何正在进行的工作流程停止的能力,同时保持连续的业务运营并保护人员、资源、资产和整体仓库权益。通过同样的谈话,业务弹性系统(BRS)是智能软件和硬件结合在一个集成系统中的组合。这种业务弹性系统的集成组合超越了灾难恢复(DR),通过提供灾后策略来避免代价高昂的停机时间,支持漏洞,并在任何企业或组织的日常工作流程操作面临额外的意外破坏时维持业务运营。随着人工智能(AI)的最新技术进步,加上机器学习(ML)和深度学习子系统,他们提出了一个人工智能系统(AIS),现在将BRS和AIS这两个系统集成在一起,可以提供一个组织或企业可以拥有的最智能的系统。为了有最好的解决方案,有最好的预测技术,从而预防和不良事件,基于人工智能深度学习中的集体历史数据。在本文中,我们介绍了这些系统中的每一个,即BRS和AIS,以及它们如何通过集成作为一个整体系统以及它们的软件、硬件、机器学习和深度学习的子系统而相互受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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