Log in to save to my catalogue

Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expressi...

Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expressi...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c7cf7f142d1848eda7b71e2e5ee7618c

Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expression programming (GEP): A case study from an iron ore mine

About this item

Full title

Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expression programming (GEP): A case study from an iron ore mine

Publisher

AIMS Press

Journal title

AIMS geosciences, 2023-01, Vol.9 (2), p.357-381

Language

English

Formats

Publication information

Publisher

AIMS Press

More information

Scope and Contents

Contents

Mine blasting can have a destructive effect on the environment. Among these effects, air overpressure (AOp) is a major concern. Therefore, a careful assessment of the AOp intensity should be conducted before any blasting operation in order to minimize the associated environmental detriment. Several empirical models have been established to predict...

Alternative Titles

Full title

Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expression programming (GEP): A case study from an iron ore mine

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_c7cf7f142d1848eda7b71e2e5ee7618c

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c7cf7f142d1848eda7b71e2e5ee7618c

Other Identifiers

ISSN

2471-2132

E-ISSN

2471-2132

DOI

10.3934/geosci.2023019

How to access this item