Dynamic control for safety system multi-agent system with case-based reasoning

被引：0

作者：

Aissani N. ^{[1
]}

Guetarni I.H.M. ^{[1
]}

Zebirate S. ^{[1
]}

机构：

[1] Laboratoire de l’Ingénierie de la sécurité des procèdes et d’environnement, Institute of Maintenance and Industrial Safety, Université Mohamed Ben Ahmed Oran 2, Bir El Djir

来源：

International Journal of Reliability and Safety | 2017年 / 11卷 / 3-4期

关键词：

Case-based reasoning; Decision making; Dynamic system; Event tree; Factors for semantic weighting; Multi-agent architecture; Ontology; Safety industrial system; Semantic network; Similarity for case retrieval;

D O I：

10.1504/IJRS.2017.089708

中图分类号：

学科分类号：

摘要：

The increasing complexity and size of electronic systems in industry, combined with growing market demand, requires industries to implement an efficient safety system to preserve equipment viability, environment protection and especially human life protection. The aim of this paper is to present a dynamic safety system based on a multi-agent paradigm using case-based reasoning to identify and react to risks. To develop the base of cases, an exhaustive risk analysis was carried out, giving rise to risk ontology and their precursors. Then, a model for identifying the similarities between precursors was developed. Case-based reasoning is very reactive, and with the presented model of similarity, the developed security system was very reactive against the risks that the system was experiencing during the experiments. Copyright © 2017 Inderscience Enterprises Ltd.

引用

页码：238 / 255

页数：17

共 35 条

[1]

Aamodt A., Plaza E., Case-based reasoning: Foundational issues, methodological variations, and system approaches, Artificial Intelligence Communications, 7, 1, pp. 39-52, (1994)

[2]

Aissani N., Beldjilali B., Dynamic scheduling of maintenance tasks in the petroleum industry: A reinforcement approach, Engineering Applications of Artificial Intelligence, 22, 7, pp. 1089-1103, (2009)

[3]

Amor S.B., Martel J.M., Guitouni A., A multicriteria risk measure in a military context: Application to the commander’s advisory system for airspace protection case, International Journal of Risk Assessment and Management, 19, 3, pp. 194-213, (2016)

[4]

Aronson J.E., Liang T.P., Turban E., Decision Support Systems and Intelligent Systems, (2005)

[5]

Bani M.S., Rashid Z.A., Hamid K.H.K., Harbawi M.E., Alias A.B., Aris M.J., The development of decision support system for waste management: A review, World Academy of Science, Engineering and Technology, 49, (2009)

[6]

Ding Z., Wang Y., Zou P.X., An agent based environmental impact assessment of building demolition waste management: Conventional versus green management, Journal of Cleaner Production, (2016)

[7]

Ellouzi H., Ltifi H., Ben Ayed M., Multi-agent modelling of decision support systems based on visual data mining, Multiagent and Grid Systems, 13, 1, pp. 31-45, (2017)

[8]

Summary Methodology, Accidents at Work Statistics, (2013)

[9]

Faghihinia E., Mollaverdi N., A multi-criterion decision-making on preventive maintenance, Proceedings of The 2012 International Conference on Industrial Engineering and Operations Management, (2015)

[10]

Giglio D., Minciardi R., Pizzorni D., Rudari R., Sacile R., Tomasoni A., Trasforini E., Towards a decision support system for real time risk assessment of hazardous material transport on road, Proceeding IEMSS, pp. 1-6, (2004)

← 1 2 3 4 →