Rock slope fuzzy stochastic damage study
Advanced Materials Research, ISSN: 1022-6680, Vol: 524-527, Page: 337-340
2012
- 7Citations
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations7
- Citation Indexes7
- CrossRef6
Conference Paper Description
Fuzzy sub-space, with analysis on generalized uncertainty of damage, is setup in this paper when topological consistency of damage fuzzy and randomness on [0,1] scale being demonstrated deeply. Furthermore, deduced under fuzzy characteristics translation are three fuzzy analytical models of damage functional, namely, half depressed distribution, swing distribution, combined swing distribution, by which, fuzzy extension territory on damage evolution is formulated here. With the representation of damage variable β probabilistic distribution as well as formulation on stochastic sub-space of damage variable, expended on the basis of extension criterion and fuzzy probability is damage model defined within generalized uncertain space, by which, introduced is fuzzy probabilistic integral algorithm of generalized uncertain damage variable that could be simulated by the forthcoming fuzzy stochastic damage constitution model based on three fuzzy functional models before. Moreover, in order to realize the joint of fuzzy input and output procedure on generalized uncertain damage variable calculation, fuzzy self-adapting stochastic damage reliability algorithm is, with the update on fuzzy stochastic finite element method within standard normal distribution probabilistic space by the help of foregoing fuzzy stochastic damage constitution model, offered in this paper on the basis of equivalent-normalization and orthogonal design theory. © (2012) Trans Tech Publications.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84861592498&origin=inward; http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.337; https://www.scientific.net/AMR.524-527.337; https://www.scientific.net/AMR.524-527.337.pdf; http://www.scientific.net/AMR.524-527.337; http://www.scientific.net/AMR.524-527.337.pdf; https://dx.doi.org/10.4028/www.scientific.net/amr.524-527.337
Trans Tech Publications, Ltd.
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know