Information Diffusion Techniques and Small-Sample Problem

Huang, Chongfu

doi:10.1142/s0219622002000142

Cited by 57 publications

(34 citation statements)

References 21 publications

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“…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). The use of information diffusion for fuzzy mathematics can be illustrated as follows (Huang, 2002 …”

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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Section: Normal Diffusion Technique For Risk Assessmentmentioning

confidence: 99%

Multiple Internet of Intelligences for Risk Analysis

Huang¹

2014

JRACR

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“…The information diffusion theory helps extract the useful underlying information from the sample as much as possible, improving system recognition accuracy (Huang, 2002;Palm, 2007).…”

Section: Q Li: Fuzzy Approach To Analysis Of Flood Riskmentioning

confidence: 99%

Fuzzy approach to analysis of flood risk based on variable fuzzy sets and improved information diffusion methods

2013

Nat. Hazards Earth Syst. Sci.

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The predictive analysis of natural disasters and their consequences is challenging because of uncertainties and incomplete data. The present article studies the use of variable fuzzy sets (VFS) and improved information diffusion method (IIDM) to construct a composite method. The proposed method aims to integrate multiple factors and quantification of uncertainties within a consistent system for catastrophic risk assessment. The fuzzy methodology is proposed in the area of flood disaster risk assessment to improve probability estimation. The purpose of the current study is to establish a fuzzy model to evaluate flood risk with incomplete data sets. The results of the example indicate that the methodology is effective and practical; thus, it has the potential to forecast the flood risk in flood risk management

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“…According to the principle of information diffusion, (Huang, 2002), we can increase the certainty of the determined relation if we increase the number of the training examples with the help of an appropriate information scattering function. ANN trained in this manner are called diffusion neural networks (e.g.…”

Section: Artificial Neural Network Approximationmentioning

confidence: 99%

Relationship between isoseismal area and magnitude of historical earthquakes in Greece by a hybrid fuzzy neural network method

Tselentis

Sokos

2012

Nat. Hazards Earth Syst. Sci.

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Abstract. In this paper we suggest the use of diffusionneural-networks, (neural networks with intrinsic fuzzy logic abilities) to assess the relationship between isoseismal area and earthquake magnitude for the region of Greece. It is of particular importance to study historical earthquakes for which we often have macroseismic information in the form of isoseisms but it is statistically incomplete to assess magnitudes from an isoseismal area or to train conventional artificial neural networks for magnitude estimation. Fuzzy relationships are developed and used to train a feed forward neural network with a back propagation algorithm to obtain the final relationships. Seismic intensity data from 24 earthquakes in Greece have been used. Special attention is being paid to the incompleteness and contradictory patterns in scanty historical earthquake records. The results show that the proposed processing model is very effective, better than applying classical artificial neural networks since the magnitude macroseismic intensity target function has a strong nonlinearity and in most cases the macroseismic datasets are very small.

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Information Diffusion Techniques and Small-Sample Problem

Cited by 57 publications

References 21 publications

Multiple Internet of Intelligences for Risk Analysis

Multiple Internet of Intelligences for Risk Analysis

Fuzzy approach to analysis of flood risk based on variable fuzzy sets and improved information diffusion methods

Relationship between isoseismal area and magnitude of historical earthquakes in Greece by a hybrid fuzzy neural network method

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