Case Reasoning Research of Emergency Network Opinion Based on Ontology

Xu, Beibei; Kuzminykh, Valeriy; Zhu, Shengqi; Jia, Yu; Zhang, Mingiun; Li, Sisi; Liu, Cuiqin

doi:10.1109/iscid.2019.00009

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Qinghua proposed a spatiotemporal expression model of structured multidimensional grid emergency cases and unified management and expression of spatiotemporal attribute characteristics and non-spatiotemporal attribute characteristics of cases [28]. Xu et al analyzed an emergency case ontology model based on process description and used three-level ontology structure to describe the attribute information of the case, so that it can be applied to different types of emergency events [29]. ElAlami structured the case into event types, key attributes, subordinate attributes, environmental attributes, and hazard assessment attributes from the perspective of attribute characteristics.…”

Section: Theoretical Research Onmentioning

confidence: 99%

Security Optimization Management for loT-Assisted Bank Liquidity Risk Emergency Using Big Data Analytic-Based Case Reasoning

Yan

Song

2022

Wireless Communications and Mobile Computing

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In modern times, financial institutions are the core carrier of efficient operation of financial markets. With the continuous development of financial models such as IoT (Internet of Things) finance, commercial banks have made many attempts in the integration and innovation of finance and logistics, but they have also increased the types and complexity of risks they face while improving financing efficiency. It has the characteristics of great destructiveness, strong infectivity, and high complexity. The establishment of a perfect emergency security optimization management for early warning of bank liquidity risk is an important part of timely detection and effective management of liquidity risk. In order to enable decision makers to accurately use the effective disposal of similar liquidity risk emergencies as a reference for decision-making, this paper studies the generation method of emergency security plan for bank liquidity risk using big data analytic-based case reasoning. Firstly, analyze the characteristics of various types of bank liquidity emergencies a, and identify the key risk points, and form the accident case database. Secondly, carry out the interval division according to the different numerical distribution characteristics of the indicators, and calculate the repeatability of the involved stages. Finally, calculate the comprehensive similarity to obtain the emergency security plan for reference. At the same time, taking A commercial bank as an example, verify the effectiveness of the method by using the constructed case-based reasoning model to generate emergency security plans intelligently. It provides reference for commercial bank liquidity risk management.

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Section: Theoretical Research Onmentioning

confidence: 99%