Application of big data and machine learning approaches to improve decision making during crises

Ali, MB ORCID: https://orcid.org/0000-0001-5854-8245 2022, 'Application of big data and machine learning approaches to improve decision making during crises' , in: Future Role of Sustainable Innovative Technologies in Crisis Management , Information Science Reference, pp. 59-70.

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Abstract

As an occurrence that jeopardises vital national interests or the basic needs of the populace, a crisis necessitates rapid decision-making and coordination between various departments and agencies in order to resolve it effectively. As a result, crisis and disaster management systems are necessary and critical. Crisis and disaster response systems are intricate, requiring numerous phases, techniques, and resources. These systems require useful and necessary data that can be used to make future decisions more effectively, such as historical and current data on crises. The use of machine learning and big data technologies to process data from crises and disasters has the potential to yield significant results in this area. The first section of this document discusses crisis management systems and available tools, such as big data and machine learning. Additionally, a machine learning and big data approach to crisis management systems were developed, which included a description and experiments, as well as a discussion of the findings and the field's future directions.

Item Type: Book Section
Schools: Schools > Salford Business School
Journal or Publication Title: Future Role of Sustainable Innovative Technologies in Crisis Management
Publisher: Information Science Reference
ISBN: 9781799898153
Depositing User: Dr Mohammed Ali
Date Deposited: 12 Sep 2022 09:21
Last Modified: 12 Sep 2022 09:21
URI: https://usir.salford.ac.uk/id/eprint/64806

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