DOIAbstract
3noopenopenErtuncay, Deniz; De Lorenzo, Andrea; Costa, GiovanniErtuncay, Deniz; De Lorenzo, Andrea; Costa, Giovann
3noopenopenErtuncay, Deniz; De Lorenzo, Andrea; Costa, GiovanniErtuncay, Deniz; De Lorenzo, Andrea; Costa, Giovann
AbstractBlast-induced ground vibration is one of the inevitable outcomes of blasting in mining proje...
As seismic networks continue to spread and monitoring sensors become more ef¿cient, the abundance of...
Neural networks are powerful and elegant computational tools that can be used in the analysis of geo...
We report on the implementation of an automatic system able to discriminate between explosion-genera...
The seismic network set up in the Hyblean Plateau (Southeastern Sicily) in the framework of the POSE...
The purpose of this article is to demonstrate the use of feedforward neural networks (FFNNs), adapti...
Pattern recognition belongs to a class of Problems which are easily solved by humans, but difficult ...
This paper reports on the classification of earthquakes and false events (thunders, quarry blasts an...
In this article we report on the implementation of an automatic system for discriminating landslide...
Abstract We present a new strategy for reliable automatic classification of local seismic signals an...
This paper reports on the classification of earthquakes and false events (thunders, quarry blasts an...
Blast-induced ground vibration is one of the inevitable outcomes of blasting in mining projects and ...
The automatic discrimination of seismic signals is an important practical goal for earth-science obs...
Abstract An artificial neural network-based pattern classification system is applied to seismic even...
Despite of technological advancement in the field of rock breakage, blasting is still an economical ...
AbstractBlast-induced ground vibration is one of the inevitable outcomes of blasting in mining proje...
As seismic networks continue to spread and monitoring sensors become more ef¿cient, the abundance of...
Neural networks are powerful and elegant computational tools that can be used in the analysis of geo...
We report on the implementation of an automatic system able to discriminate between explosion-genera...
The seismic network set up in the Hyblean Plateau (Southeastern Sicily) in the framework of the POSE...
The purpose of this article is to demonstrate the use of feedforward neural networks (FFNNs), adapti...
Pattern recognition belongs to a class of Problems which are easily solved by humans, but difficult ...
This paper reports on the classification of earthquakes and false events (thunders, quarry blasts an...
In this article we report on the implementation of an automatic system for discriminating landslide...
Abstract We present a new strategy for reliable automatic classification of local seismic signals an...
This paper reports on the classification of earthquakes and false events (thunders, quarry blasts an...
Blast-induced ground vibration is one of the inevitable outcomes of blasting in mining projects and ...
The automatic discrimination of seismic signals is an important practical goal for earth-science obs...
Abstract An artificial neural network-based pattern classification system is applied to seismic even...
Despite of technological advancement in the field of rock breakage, blasting is still an economical ...
AbstractBlast-induced ground vibration is one of the inevitable outcomes of blasting in mining proje...
As seismic networks continue to spread and monitoring sensors become more ef¿cient, the abundance of...
Neural networks are powerful and elegant computational tools that can be used in the analysis of geo...
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