Related references
Note: Only part of the references are listed.Airblast prediction through a hybrid genetic algorithm-ANN model
Danial Jahed Armaghani et al.
NEURAL COMPUTING & APPLICATIONS (2018)
The potential application of particle swarm optimization algorithm for forecasting the air-overpressure induced by mine blasting
Amir AminShokravi et al.
ENGINEERING WITH COMPUTERS (2018)
Optimizing Blasting's Air Overpressure Prediction Model using Swarm Intelligence
Mohd Nur Asmawisham Alel et al.
INTERNATIONAL SEMINAR ON MATHEMATICS AND PHYSICS IN SCIENCES AND TECHNOLOGY 2017 (ISMAP 2017) (2018)
Two-phase clustering algorithm with density exploring distance measure
Jingjing Ma et al.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY (2018)
Evaluation of blast-induced ground vibrations in open-pit mines by using adaptive neuro- fuzzy inference systems
Arzu Kocaslan et al.
ENVIRONMENTAL EARTH SCIENCES (2017)
A new kernel method for hyperspectral image feature extraction
Bin Zhao et al.
GEO-SPATIAL INFORMATION SCIENCE (2017)
Urban land-use classification by combining high-resolution optical and long-wave infrared images
Xuehua Guan et al.
GEO-SPATIAL INFORMATION SCIENCE (2017)
Repurposing a deep learning network to filter and classify volunteered photographs for land cover and land use characterization
Lukasz Tracewski et al.
GEO-SPATIAL INFORMATION SCIENCE (2017)
Several non-linear models in estimating air-overpressure resulting from mine blasting
Mahdi Hasanipanah et al.
ENGINEERING WITH COMPUTERS (2016)
A combination of the ICA-ANN model to predict air-overpressure resulting from blasting
Danial Jahed Armaghani et al.
ENGINEERING WITH COMPUTERS (2016)
A new combination of artificial neural network and K-nearest neighbors models to predict blast-induced ground vibration and air-overpressure
Maryam Amiri et al.
ENGINEERING WITH COMPUTERS (2016)
Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique
Edy Tonnizam Mohamad et al.
ENVIRONMENTAL EARTH SCIENCES (2016)
Prediction of blast boulders in open pit mines via multiple regression and artificial neural networks
Ghiasi Majid et al.
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY (2016)
Neuro-fuzzy technique to predict air-overpressure induced by blasting
Danial Jahed Armaghani et al.
ARABIAN JOURNAL OF GEOSCIENCES (2015)
Analysis of blasting damage in adjacent mining excavations
Nick Yugo et al.
JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING (2015)
Prediction of airblast-overpressure induced by blasting using a hybrid artificial neural network and particle swarm optimization
M. Hajihassani et al.
APPLIED ACOUSTICS (2014)
Root mean square error (RMSE) or mean absolute error (MAE)? - Arguments against avoiding RMSE in the literature
T. Chai et al.
GEOSCIENTIFIC MODEL DEVELOPMENT (2014)
Prediction of Backbreak in Open-Pit Blasting Operations Using the Machine Learning Method
Manoj Khandelwal et al.
ROCK MECHANICS AND ROCK ENGINEERING (2013)
Sizing of rock fragmentation modeling due to bench blasting using adaptive neuro-fuzzy inference system (ANFIS)
Karami Alireza et al.
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY (2013)
Prediction of flyrock in open pit blasting operation using machine learning method
Manoj Khandelwal et al.
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY (2013)
Evaluation of blast induced ground vibration for minimizing negative effects on surrounding structures
Reza Nateghi
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING (2012)
Comparison of intelligence science techniques and empirical methods for prediction of blasting vibrations
M. Mohamadnejad et al.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2012)
Sizing of rock fragmentation modeling due to bench blasting using adaptive neuro-fuzzy inference system and radial basis function
Karami Alireza et al.
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY (2012)
Prediction and controlling of flyrock in blasting operation using artificial neural network
M. Monjezi et al.
ARABIAN JOURNAL OF GEOSCIENCES (2011)
Prediction of blast-induced ground vibration using artificial neural networks
M. Monjezi et al.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2011)
Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
Andrea Saltelli et al.
COMPUTER PHYSICS COMMUNICATIONS (2010)
Estimation of blast induced peak particle velocity at underground mine structures originating from neighbouring surface mine
D. Deb et al.
TRANSACTIONS OF THE INSTITUTIONS OF MINING AND METALLURGY SECTION A-MINING TECHNOLOGY (2010)
Operational and geological parameters in the assessing blast induced airblast-overpressure in quarries
C. Kuzu et al.
APPLIED ACOUSTICS (2009)
Application of two non-linear prediction tools to the estimation of tunnel boring machine performance
S. Yagiz et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2009)
Ground vibration isolation with geofoam barriers: Centrifuge modeling
C. Murillo et al.
GEOTEXTILES AND GEOMEMBRANES (2009)
Artificial neural network for prediction and control of blasting vibrations in Assiut (Egypt) limestone quarry
Mostafa Tantawy Mohamed
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2009)
Evaluation of effect of blasting pattern parameters on back break using neural networks
M. Monjezi et al.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2008)
Predicting the effectiveness of blast wall barriers using neural networks
Alex M. Remennikov et al.
INTERNATIONAL JOURNAL OF IMPACT ENGINEERING (2007)
Estimating the approximation error when fixing unessential factors in global sensitivity analysis
I. M. Sobol et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2007)
Estimation of rock modulus: For intact rocks with an artificial neural network and for rock masses with a new empirical equation
H Sonmez et al.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2006)
Multilayer perceptron-based DFE with lattice structure
A Zerguine et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2001)
Share Paper
