Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning

Masoud Mohammadian

doi:10.1007/978-3-642-33412-2_16

Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning

Masoud Mohammadian

Canberra Business School

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

Development and management of disaster recovery plan for IT systems are complex, demanding, and yet crucial to an organization success and its competitive position in the marketplace. Due to rapid changes in emerging technologies there is a need for constant improvement and adjustment to disaster recovery plans for IT systems. There are a large number of processes involved in disaster recovery planning for IT system. The interdependencies of these processes make it very difficult for Chief Information Officers (CIOs) to comprehend and be aware of effect of inefficiencies that may exist in development of these processes in the disaster recovery plan of their organization. This paper considers the implementation of a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in implementing a disaster recovery plan for IT systems and their related processes to improve the understanding of CIOs about the systems and its associated risks

Original language	English
Title of host publication	International Conference on Artificial Intelligence Applications and Innovations
Editors	Lazaros lliadis, llias Maglogiannis, Harris Papadopoulos
Place of Publication	UK
Publisher	Springer
Pages	155-165
Number of pages	11
Volume	382
ISBN (Print)	9783642334085
DOIs	https://doi.org/10.1007/978-3-642-33412-2_16
Publication status	Published - 2012
Event	International Conference on Artificial Intelligence Applications and Innovations - Halkidiki, Halkidiki, Greece Duration: 27 Sept 2012 → 30 Sept 2012

Conference

Conference	International Conference on Artificial Intelligence Applications and Innovations
Country/Territory	Greece
City	Halkidiki
Period	27/09/12 → 30/09/12

Access to Document

10.1007/978-3-642-33412-2_16

http://dl.ifip.org/db/conf/ifip12/aiai2012-2/Mohammadian12.pdf

Cite this

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title = "Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning",

abstract = "Development and management of disaster recovery plan for IT systems are complex, demanding, and yet crucial to an organization success and its competitive position in the marketplace. Due to rapid changes in emerging technologies there is a need for constant improvement and adjustment to disaster recovery plans for IT systems. There are a large number of processes involved in disaster recovery planning for IT system. The interdependencies of these processes make it very difficult for Chief Information Officers (CIOs) to comprehend and be aware of effect of inefficiencies that may exist in development of these processes in the disaster recovery plan of their organization. This paper considers the implementation of a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in implementing a disaster recovery plan for IT systems and their related processes to improve the understanding of CIOs about the systems and its associated risks",

author = "Masoud Mohammadian",

year = "2012",

doi = "10.1007/978-3-642-33412-2_16",

language = "English",

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editor = "Lazaros lliadis and llias Maglogiannis and Harris Papadopoulos",

booktitle = "International Conference on Artificial Intelligence Applications and Innovations",

publisher = "Springer",

address = "Netherlands",

note = "International Conference on Artificial Intelligence Applications and Innovations ; Conference date: 27-09-2012 Through 30-09-2012",

}

Mohammadian, M 2012, Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning. in L lliadis, L Maglogiannis & H Papadopoulos (eds), International Conference on Artificial Intelligence Applications and Innovations. vol. 382, Springer, UK, pp. 155-165, International Conference on Artificial Intelligence Applications and Innovations, Halkidiki, Greece, 27/09/12. https://doi.org/10.1007/978-3-642-33412-2_16

Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning. / Mohammadian, Masoud.
International Conference on Artificial Intelligence Applications and Innovations. ed. / Lazaros lliadis; llias Maglogiannis; Harris Papadopoulos. Vol. 382 UK: Springer, 2012. p. 155-165.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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T1 - Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning

AU - Mohammadian, Masoud

PY - 2012

Y1 - 2012

N2 - Development and management of disaster recovery plan for IT systems are complex, demanding, and yet crucial to an organization success and its competitive position in the marketplace. Due to rapid changes in emerging technologies there is a need for constant improvement and adjustment to disaster recovery plans for IT systems. There are a large number of processes involved in disaster recovery planning for IT system. The interdependencies of these processes make it very difficult for Chief Information Officers (CIOs) to comprehend and be aware of effect of inefficiencies that may exist in development of these processes in the disaster recovery plan of their organization. This paper considers the implementation of a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in implementing a disaster recovery plan for IT systems and their related processes to improve the understanding of CIOs about the systems and its associated risks

AB - Development and management of disaster recovery plan for IT systems are complex, demanding, and yet crucial to an organization success and its competitive position in the marketplace. Due to rapid changes in emerging technologies there is a need for constant improvement and adjustment to disaster recovery plans for IT systems. There are a large number of processes involved in disaster recovery planning for IT system. The interdependencies of these processes make it very difficult for Chief Information Officers (CIOs) to comprehend and be aware of effect of inefficiencies that may exist in development of these processes in the disaster recovery plan of their organization. This paper considers the implementation of a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in implementing a disaster recovery plan for IT systems and their related processes to improve the understanding of CIOs about the systems and its associated risks

U2 - 10.1007/978-3-642-33412-2_16

DO - 10.1007/978-3-642-33412-2_16

M3 - Conference contribution

SN - 9783642334085

VL - 382

SP - 155

EP - 165

BT - International Conference on Artificial Intelligence Applications and Innovations

A2 - lliadis, Lazaros

A2 - Maglogiannis, llias

A2 - Papadopoulos, Harris

PB - Springer

CY - UK

T2 - International Conference on Artificial Intelligence Applications and Innovations

Y2 - 27 September 2012 through 30 September 2012

ER -

Artificial Intelligence Applications for Risk Analysis, Risk Prediction and Decision Making in Disaster Recovery Planning

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