Robust Geotechnical Design of Earth Slopes Using Fuzzy Sets

Gong, Wenping; Wang, Lei; Khoshnevisan, Sara; Juang, C. Hsein; Huang, Hongwei; Zhang, Jie

doi:10.1061/(asce)gt.1943-5606.0001196

Cited by 67 publications

(21 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the implementation of the computation is not trivial, as the algebraic solution procedure may be complicated and may not guarantee a result. Therefore, the vertex method, one of the simplest solution procedures, has been used in several studies [89,92,98,99,103].…”

Section: Fuzzy Point Estimate Methodsmentioning

confidence: 99%

“…As explained previously, in this approach, all 2 N vertex combinations at each α-cut level are used in the evaluation of the performance function. However, in previous vertex approaches [89,92,98,99,103], the outputs of performance functions were determined by taking only the minimum and maximum values obtained from 2 N vertex combinations at each α-cut level. This study therefore differs, in this way, from previous fuzzy-number-based approaches.…”

Section: Fuzzy Point Estimate Methodsmentioning

confidence: 99%

“…Fuzzy set theory has been found to be effective and suitable for modeling uncertainty in geotechnical parameters when data are insufficient to define a probability distribution fully [93]. Consequently, fuzzy set theory has been used in several site-specific slope stability analyses at hillslope scale [89,92,[94][95][96][97][98][99].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Physically Based Susceptibility Assessment of Rainfall-Induced Shallow Landslides Using a Fuzzy Point Estimate Method

2017

View full text Add to dashboard Cite

Abstract:The physically based model has been widely used in rainfall-induced shallow landslide susceptibility analysis because of its capacity to reproduce the physical processes governing landslide occurrence and a higher predictive capability. However, one of the difficulties in applying the physically based model is that uncertainties arising from spatial variability, measurement errors, and incomplete information apply to the input parameters and analysis procedure. Uncertainties have been recognized as an important cause of mismatch between predicted and observed distributions of landslide occurrence. Therefore, probabilistic analysis has been used to quantify the uncertainties. However, some uncertainties, because of incomplete information, cannot be managed satisfactorily using a probabilistic approach. Fuzzy set theory is applicable in this case. In this study, in order to handle uncertainty propagation through a physical model, fuzzy set theory, coupled with the vertex method and the point estimate method, was adopted for regional landslide susceptibility assessment. The proposed approach was used to evaluate susceptibility to rainfall-induced shallow landslides for a regional study area, and the analysis results were compared with landslide inventory to evaluate the performance of the proposed approach. The AUC values arising from the landslide susceptibility analyses using the proposed approach and probabilistic analysis were 0.734 and 0.736, respectively. However, when the COV values of the input parameters were reduced, the AUC values of the proposed approach and the probabilistic analysis were reduced to 0.722 and 0.688, respectively. It means that the performance of the fuzzy approach is similar to that of probabilistic analysis but is more robust against variation of input parameters. Thus, at catchment scale, the fuzzy approach can respond appropriately to the uncertainties inherent in physically based landslide susceptibility analysis, and is especially advantageous when the amount of quality data is very limited.

show abstract

Section: Fuzzy Point Estimate Methodsmentioning

confidence: 99%

Section: Fuzzy Point Estimate Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Physically Based Susceptibility Assessment of Rainfall-Induced Shallow Landslides Using a Fuzzy Point Estimate Method

2017

View full text Add to dashboard Cite

show abstract

“…The more recent applications are found in various fields such as mechanical, structural and aeronautical design (e.g., Chen et al 1996;Chen et al 1999;Lee and Park 2001;Doltsinis et al 2005;Park et al 2006;Brik et al 2006;Lagaros and Fragiadakis 2007;Kumar et al 2008;Marano et al 2008;Lee et al 2010). Applications to geotechnical problems were introduced by Juang and his co-workers (Juang et al 2012(Juang et al , 2013a(Juang et al , 2013bJuang and Wang 2013;Wang et al 2013Wang et al , 2014Gong et al 2014aGong et al , 2014bGong et al , 2014c. Because of the distinct characteristic of geotechnical problems, which often involves high coefficients of variation (COVs) in the noise factors (i.e., uncertain input parameters and imperfect models), the term 'RGD' was coined by Juang et al (2013b) for use in these geotechnical applications.…”

Section: Introductionmentioning

confidence: 97%

Robust design in geotechnical engineering – an update

Khoshnevisan

Gong

Wang

et al. 2014

Georisk: Assessment and Management of Risk for Engineered Syste

Self Cite

View full text Add to dashboard Cite

This paper presents an update for the robust geotechnical design (RGD) methodology, which seeks an optimal design with respect to design robustness and cost efficiency, while satisfying the safety requirements. In general, the design robustness is achieved if the system response is insensitive to the variation in the uncertain input parameters (called "noise factors"). In other words, a design is considered robust if the system response exhibits little variation, even though there is high variation in the input parameters. Robust design achieves this desirable outcome by carefully adjusting 'design parameters' (i.e., the parameters that can be controlled by the designer, such as the geometry and dimensions) without reducing the uncertainty in the noise factors. In this paper, the existing RGD methodology is updated with a gradient-based robustness measure and a simplified procedure for seeking the knee point. The RGD methodology and its simplified version (with new updates) are illustrated with three design examples. The results presented in this paper show that the RGD methodology and its simplified version are effective design tools that considers safety, cost and design robustness simultaneously. The advantages of the simplified RGD approach are discussed.

show abstract

“…Due to the uncertainty and fuzziness of the evaluated variables, the fuzzy set theory was introduced into DEA/AR model. In fact, the fuzzy based methodology has been increasingly used to analyze and evaluate the stability of the rock or soil body, because of its ability in considering the uncertainty and complexity of rocks or soils (Basarir et al, 2014;Xu et al, 2014;Gong et al, 2015). In the proposed model, various input and output variables were considered as fuzzy variables or certainty variables.…”

Section: Introductionmentioning

confidence: 99%