Estimating uniaxial compressive strength of rocks using genetic expression programming

Özbek, Ahmet; Ünsal, Mehmet; Dikec, Aydin

doi:10.1016/j.jrmge.2013.05.006

Cited by 66 publications

(14 citation statements)

References 6 publications

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“…Unlike GP and GA techniques that have been widely applied in the field of rock mechanics and mining engineering (Baykasoglu et al 2008;Ozbek et al 2013;Güllü 2012;Ahangari et al 2015;Dindarloo 2015a), GEP is not yet a well-established technique in the mentioned fields. GEP is the developed version of GP and GA and can surmount their shortcomings such as difficulties of applying genetic operators on trees (Ferreira 2001;Baykasoglu et al 2008;Teodorescu and Sherwood 2008).…”

Section: Gene Expression Programmingmentioning

confidence: 99%

“…Teodorescu and Sherwood 2008;Alkroosh and Nikraz 2011;Mollahasani et al 2011;Ozbek et al 2013). GEP is a new algorithm which can introduce relationships between input parameters to estimate output.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Baykasoglu et al (2008) andÇ anakcı et al (2009) proposed new models based on GEP for solving problems related to compressive and tensile strength of the rock with high degree of accuracy. Ozbek et al (2013) and Dindarloo and Siami-Irdemoosa (2015) developed GEP models for prediction of the uniaxial compressive strength (UCS) of the rock samples. Their study represented a good agreement between the measured UCS and predicted by GEP model.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Faradonbeh

Armaghani

Majid

et al. 2016

Int. J. Environ. Sci. Technol.

149

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Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.

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Section: Gene Expression Programmingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Faradonbeh

Armaghani

Majid

et al. 2016

Int. J. Environ. Sci. Technol.

149

View full text Add to dashboard Cite

show abstract

“…This method was firstly introduced by Ferreira [78]. Recently, the application of this method has increased in civil and mining engineering [7,67,[79][80][81][82][83][84]. With the use of different mathematical operators and linear functions (e.g., +, −, sin, tan, cos, sqrt, x 2 , and x 3 ), this method forms a mathematical relation between the input and output variables.…”

Section: Gene Expression Programming (Gep)mentioning

confidence: 99%

Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

et al. 2020

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Peak particle velocity (PPV) is a critical parameter for the evaluation of the impact of blasting operations on nearby structures and buildings. Accurate estimation of the amount of PPV resulting from a blasting operation and its comparison with the allowable ranges is an integral part of blasting design. In this study, four quarry sites in Malaysia were considered, and the PPV was simulated using gene expression programming (GEP) and Monte Carlo simulation techniques. Data from 149 blasting operations were gathered, and as a result of this study, a PPV predictive model was developed using GEP to be used in the simulation. In order to ensure that all of the combinations of input variables were considered, 10,000 iterations were performed, considering the correlations among the input variables. The simulation results demonstrate that the minimum and maximum PPV amounts were 1.13 mm/s and 34.58 mm/s, respectively. Two types of sensitivity analyses were performed to determine the sensitivity of the PPV results based on the effective variables. In addition, this study proposes a method specific to the four case studies, and presents an approach which could be readily applied to similar applications with different conditions.

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“…Najučinkovitiju procjenu pokazao je LGP model evolucijskog programiranja [48]. Ozbeka sa suradnicima opisao je upotrebu GEP modela za procjenu UCS bazalta i tufa te pokazao dobro slaganje između eksperimentalno utvrđenih podataka i rezultata postignutih procjenom [49]. Beiki i suradnici su na temelju genetskog programiranja načinili modele za procjenu UCS i E karbonatnih stijena na temelju rezultata ispitivanja uzoraka prikupljenih na Asmary formaciji u Iranu [50].…”

Section: Procjena Pomoću Evolucijskog Programiranjaunclassified

Modeli za procjenu jednoosne tlačne čvrstoće i modula elastičnosti

Briševac¹,

Hrženjak²,

Buljan³

2016

JCE

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Modeli za procjenu jednoosne tlačne čvrstoće i modula elastičnosti U ovom radu ukratko je izložen pregled najznačajnijih metoda za procjenu jednoosne tlačne čvrstoće i Yangovog modula elastičnosti intaktnog stijenskog materijala koje su nastale u okviru mnogobrojnih istraživanja. Iznesen je prijedlog podjele metoda prema kojemu se one u osnovi mogu podijeliti na jednostavne i složene metode. Jednostavne metode uključuju različite dijagrame i tablice te primjenu jednadžbi jednostruke regresije, a složene metode uključuju primjene jednadžbi višestruke regresije, modela neizrazite logike, neuronskih mreža, evolucijskog programiranja i regresijskog stabla. Models for estimating uniaxial compressive strength and elastic modulusThe most significant methods for estimating the uniaxial compressive strength and Young's modulus of intact rock material, formulated in the scope of numerous previous studies, are briefly presented in the paper. The proposal for classification of these methods, according to which they can generally be divided into simple and complex methods, is also presented. Simple methods include various diagrams and tables and the use of simple regression equations, while complex methods comprise the use of multiple regression equations, fuzzy logic models, neural networks, evolutionary programming, and regression trees.

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Estimating uniaxial compressive strength of rocks using genetic expression programming

Cited by 66 publications

References 6 publications

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

Modeli za procjenu jednoosne tlačne čvrstoće i modula elastičnosti

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