English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Pillars are important structural units used to ensure mining safety inunderground hard rock mines. Therefore, precise predictions regarding thestability of underground pillars are required. One common index that is oftenused to assess pillar stability is the Safety Factor (SF). Unfortunately, suchcrisp boundaries in pillar stability assessment using SF are unreliable. Thispaper presents a novel application of Artificial Neural Network-Backpropagation(ANN-BP) and Deep Ensemble Learning for pillar stability classification. Thereare three types of ANN-BP used for the classification of pillar stabilitydistinguished by their activation functions: ANN-BP ReLU, ANN-BP ELU, andANN-BP GELU. This research also presents a new labeling alternative for pillarstability by considering its suitability with the SF. Thus, pillar stability isexpanded into four categories: failed with a suitable safety factor, intactwith a suitable safety factor, failed without a suitable safety factor, andintact without a suitable safety factor. There are five inputs used for eachmodel: pillar width, mining height, bord width, depth to floor, and ratio. Theresults showed that the ANN-BP model with Ensemble Learning could improveANN-BP performance with an average accuracy of 86.48% and an F_2-score of96.35% for the category of failed with a suitable safety factor.

Ensemble Learning Model on Artificial Neural Network-Backpropagation (ANN-BP) Architecture for Coal Pillar Stability Classification