Titlebook: Information Granularity, Big Data, and Computational Intelligence; Witold Pedrycz,Shyi-Ming Chen Book 2015 Springer International Publishi

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JADED

How to Understand Connections Based on Big Data: From Cliques to Flexible Granulesost favorable outcome. To be able to do that, we need to have a quantitative model describing how the values of the desired quantities change—and for that, we need to know which factors influence this change. Usually, these factors are selected by using traditional statistical techniques, but with t

膽小懦夫

Graph-Based Framework for Evaluating the Feasibility of Transition to Maintainomicsuracy and the ability to offer tracking information led to the augmentation of e-technologies’ applications within maintenance management, i.e., e-maintenance. However, like any other information and communication (ICT)-based operation, massive data sets (i.e., big data) are generated from videos, a

軟弱

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The Property of Different Granule and Granular Methods Based on Quotient Spaceo describe or present objects is the base to solve questions frequently. So we suppose that a problem solving space, or a problem space for short, is described by a triplet (.,?.,?.), and assume that . is a domain, . is an equivalence relation on ., . is a topology of ., [.] is a quotient set under

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Building Fuzzy Robust Regression Model Based on Granularity and Possibility Distributionerval for a granular instead of a single numerical value. This granular provides the wider treatment for us to human-centered understanding of the latent system. Such a granule or interval of fuzzy regression model is created by considering how far a sample is from the central values. That means whe