Artificial Neural Network

Modestus O. Okwu, Lagouge K. Tartibu

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

15 Citations (Scopus)

Abstract

Artificial Neural Networks (ANNs) are known to be one of the most prevalent intelligent systems whose architecture is modeled by mimicking the human brain. Most of the real-life problems that has been solved so far followed the dimension of natural systems. ANN model has been developed and tested in a blasting operation. Blasting operations can damage mine plant and structure, especially in cases where the design has not been done properly particularly if the vibrations induced are sufficiently high. Therefore, prediction of the peak particle velocity (PPV) resulting from the blasting operations in an open-pit mine is necessary. Dataset obtained from a mine plant was tested using ANN model. Considering known values of the distance between source and measurement points (D), the maximum charge per delay (WD), and scaled distance (SD), the overall regression value R2 of 0.95468 suggests that the output tracks the targets effectively, meaning that ANN model could be useful for the prediction of PPV.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Science and Business Media Deutschland GmbH
Pages133-145
Number of pages13
DOIs
Publication statusPublished - 2021

Publication series

NameStudies in Computational Intelligence
Volume927
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

ASJC Scopus subject areas

  • Artificial Intelligence

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