Fuzzy risk analysis of flood disasters based on diffused-interior-outer-set model

Qiang, Zhimin; Zhou, Jiang; Zhou, Chao; Guo, Jun; Deng, Weiping; Yang, Mengqi; Liao, Li Chun

doi:10.1016/j.eswa.2011.12.008

Cited by 46 publications

(26 citation statements)

References 25 publications

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“…Second, IDM is employed to improve the efficiency of the existing algorithms or systems with overreliance on sufficient samples, such as artificial intelligence techniques, geographical information system and variable fuzzy sets (Huang and Moraga 2004;Q. Li et al 2012;Zou et al 2012). In fact, the information diffusion function (DF) plays an essential role in guaranteeing robustness and consistency of IDM (Chongfu 1997;Xinzhou, Yangsheng, and Yongjing 2003).…”

Section: Introductionmentioning

confidence: 98%

A new information diffusion modelling technique based on vibrating string equation and its application in natural disaster risk assessment

Bai

Zhang

Mei

et al. 2014

International Journal of General Systems

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In this paper, to naturally fill the gap in incomplete data, a new algorithm is proposed for estimating the risk of natural disasters based on the information diffusion theory and the equation of the vibrating string. Two experiments are performed with small samples to investigate its effectiveness. Furthermore, to demonstrate the practicality of the new algorithm, it is applied to study the relationship between epicentral intensity and earthquake magnitude, with strong-motion earthquake observations measured in Yunnan Province in China. The regression model, the back-propagation neural network and the conventional information diffusion model are also involved for comparison. All results show that the new algorithm, which can unravel fuzzy information in incomplete data, is better than the main existing methods for risk estimation.

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Section: Introductionmentioning

confidence: 98%

A new information diffusion modelling technique based on vibrating string equation and its application in natural disaster risk assessment

Bai

Zhang

Mei

et al. 2014

International Journal of General Systems

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“…Huang [7] demonstrated the reliability of the interior outer set. The diffused interior outer set model has been proposed by Zou et al [17]. Liu and Liu [8] presented expected value of fuzzy variable and fuzzy expected value models.…”

Section: Introductionmentioning

confidence: 99%

Risk analysis in a production inventory model with fuzzy demand, variable production rate and production time dependent selling price

Patra

Mondal

2015

OPSEARCH

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In this paper a production inventory model of a single item with a variable production rate and production time dependent selling price has been introduced. Realistically it is seen that for any business concern, demand is always uncertain. Henceforth, in this model, demand of an item has been assumed to be fuzzy but its membership function is not known in prior. It is also considered that the production rate is a decreasing function of the inverse efficiency of the system. Under these circumstances, a profit function of the model has been formulated. As demand is fuzzy with unknown membership function, hence to get expected maximum profit, the diffusion method including possibility probability distribution has been used and the risk estimation values for failure to attain different profit levels have been evaluated. Finally the proposed model has been demonstrated taking a numerical example and a comparison among different types of demand such as crisp, fuzzy with triangular and trapezoidal membership value and fuzzy with unknown membership value have been shown.

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“…The interior-outer-set model, which is based on information diffusion theory, can be used to calculate a possibility-probability distribution from a small sample. This model provided better multi-valued results for flood risk management (Zou et al, 2012). Information diffusion theory was used to evaluate accident rates in dangerous chemical transportation and analyze the consequences of such accidents with GIS simulation technology (Zhang and Zhao, 2007).…”

Section: Normal Diffusion Technique For Risk Assessmentmentioning

confidence: 99%

Multiple Internet of Intelligences for Risk Analysis

Huang¹

2014

JRACR

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In this study, we define a multiple Internet of intelligences (M-IOI) as the processing of homological information in layers. If agents in an M-IOI not only provide information in response to a question asked by a customer but also review information from other agents and summarize it, we refer to this as a summarizing M-IOI. The fuzzy mathematics method of normal diffusion is suggested to transform the summaries into fuzzy sets so that a satisfactory answer to the question is given. A summarizing M-IOI is used in a case study of typhoon dynamic risk in Wenzhou, China, where an insurance company wants to know whether the level of the risk will increase significantly. The effective knowledge in a summarizing M-IOI is measured to evaluate the quality of the answer. We also discuss the relation between IOIs and a global brain.

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Fuzzy risk analysis of flood disasters based on diffused-interior-outer-set model

Cited by 46 publications

References 25 publications

A new information diffusion modelling technique based on vibrating string equation and its application in natural disaster risk assessment

A new information diffusion modelling technique based on vibrating string equation and its application in natural disaster risk assessment

Risk analysis in a production inventory model with fuzzy demand, variable production rate and production time dependent selling price

Multiple Internet of Intelligences for Risk Analysis

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