2015
DOI: 10.1016/j.tust.2015.05.003
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Stochastic assessment of pillar stability at Laisvall mine using Artificial Neural Network

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Cited by 49 publications
(19 citation statements)
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“…As a result, many researchers are looking for market forecasting capabilities in a variety of ways (Prasanna and Ezhilmaran 2013). According to previous studies, ANN seems a good and reasonably validated method in the prediction of stock price (Idris et al 2015). The three most popular ANNs for stock prediction are the recurrent neural network (RNN) (Saad et al 1998), the radial basis function (RBF) (Han et al 2001), and multilayer perceptron (MLP).…”
Section: Literature Reviewmentioning
confidence: 99%
“…As a result, many researchers are looking for market forecasting capabilities in a variety of ways (Prasanna and Ezhilmaran 2013). According to previous studies, ANN seems a good and reasonably validated method in the prediction of stock price (Idris et al 2015). The three most popular ANNs for stock prediction are the recurrent neural network (RNN) (Saad et al 1998), the radial basis function (RBF) (Han et al 2001), and multilayer perceptron (MLP).…”
Section: Literature Reviewmentioning
confidence: 99%
“…When the rock mass can be considered highly competent, pillars are usually much smaller than the rooms and the weakest rock mass between the roof, ore layer, and floor will command the opening instability. According to Idris et al (2015), a pillar can be defined as the in situ rock mass between two or more underground openings. Pillars can be composed entirely of ore or ore and waste when the ore body has a small thickness relative to the excavation height.…”
Section: Introductionmentioning
confidence: 99%
“…The estimation of the pillar strength can be done by empirical methods (Hedley and Grant, 1972;Lunder and Pakalnis, 1997;Potvin et al, 1989;Salamon and Munro, 1967;Von Kimmelmann et al, 1984) or numerical load tests (Martin and Maybee, 2000). Alternatively, safety may be inferred directly from numerical methods by means of limit strains (Alber and Heiland, 2001;Idris et al, 2015;Napa-García and Navarro Torres, 2017), averaging the strength-to-stress ratio over the pillar's section (Hoek and Brown, 1980), or by using the strength reduction method (SRM) (Navarro-Torres et al, 2011;Tulu et al, 2015). The safety factor (FS) of the pillar is then calculated by dividing the pillar strength by the average acting pillar stress, typically estimated using the tributary area approach.…”
Section: Introductionmentioning
confidence: 99%
“…The mechanical stability of pillars is critical, because their failure might induce a catastrophic event due to the lack of redundancy associated with this type of failure. According to Idris et al (2015), a pillar can be defined as the remaining rock mass between two or more underground openings. The mechanical stability of pillars has been evaluated in literature by means of empirical methods (Laubscher 1990;Bullock 2011;Lunder & Pakalnis 1997;Obert & Duvall 1967), and by numerical methods (Idris et al 2015;Gao & Ge 2016;Corkum & Board 2016;Navarro Torres et al 2011;Kortnik 2009;Jaiswal & Shrivastva 2009;Deng et al 2003;Pariseau & Eitani 1981).…”
Section: Introductionmentioning
confidence: 99%
“…Hence, the use of efficient techniques to predict design conditions is desired. The critical strain ε crit approach proposed by Sakurai (1981), and later used by several authors in order to estimate the stability of underground structures (Sakurai et al 1993;Sakurai 1997Sakurai , 1999Idris et al 2015;Aydan et al 1993), offers an attractive solution to this problem. Sakurai´s method seems to be appealing because its need to run only one typical stress-strain analysis to obtain a measurement of a stability index in terms of the mobilised strain.…”
Section: Introductionmentioning
confidence: 99%