Map** mineral prospectivity using an extreme learning machine regression

Y Chen, W Wu - Ore Geology Reviews, 2017 - Elsevier
In this research, we conduct a case study of map** polymetallic prospectivity using an
extreme learning machine (ELM) regression. A Quad-Core CPU 1.8 GHz laptop computer …

Harnessing machine learning for accurate estimation of compressive strength of high-performance self-compacting concrete from non-destructive tests: a comparative …

IK Harith, AM Abdulhadi, ML Hussien - Construction and Building Materials, 2024 - Elsevier
This study investigates the compressive strength (CS-28d) of high-performance self-
compacting concrete. To accurately estimate the CS-28d, the study employed regression …

Mendiagnosis penyakit diabetes melitus dengan menggunakan metode extreme learning machine

JJ Pangaribuan - Journal Information System Development …, 2016 - ejournal-medan.uph.edu
ABSTRAK Pada tahun 2010 lalu, World Health Organization (WHO) lewat Global Status
Report melaporkan bahwa 60 persen penyebab kematian semua umur di dunia adalah …

Harnessing machine learning for accurate estimation of concrete strength using non-destructive tests: a comparative study

IK Harith, MM AL-Rubaye, AM Abdulhadi… - … Experiments and Design, 2025 - Springer
Assessing the compressive strength of existing concrete structures is paramount for
ensuring their safety and durability. Non-destructive testing (NDT) methods, while valuable …

Robust, reliable and applicable tool wear monitoring and prognostic: approach based on an improved-extreme learning machine

K Javed, R Gouriveau, N Zerhouni… - … IEEE Conference on …, 2012 - ieeexplore.ieee.org
Although efforts in this field are significant around the world, real prognostics systems are
still scarce in industry. Indeed, it is hard to provide efficient approaches that are able to …

Production multivariate outlier detection using principal components

PM O'Neill - 2008 IEEE International Test Conference, 2008 - ieeexplore.ieee.org
Various aspects of using principal component and related analyses to detect outliers in
multiple analog measurements made on digital CMOS circuits were investigated. The focus …

Diagnosis of diabetes mellitus using extreme learning machine

JJ Pangaribuan - 2014 International Conference on …, 2014 - ieeexplore.ieee.org
In 2010, Global Status Report on NCD World Health Organization (WHO) reported that 60
percent of deaths in the world caused by the non-communicable diseases, and one of the …

Discrimination of Grey Cast Iron morphology using integrated SVM and ANN approaches

A Khaled, MRA Atia, T Moussa - 2017 Intelligent Systems …, 2017 - ieeexplore.ieee.org
The internal structure of Grey Cast Iron (GCI) and its microstructure determines the
acceptance or rejection of several mechanical parts in the inspection process. This is based …

Predictive modeling of material properties using GMDH-based Abductive networks

IA Lawal, YO Mohammed - 2011 Fifth Asia Modelling …, 2011 - ieeexplore.ieee.org
Material properties are very important in most material science and engineering
computations. A number of modeling and machine learning techniques have been used for …

[引用][C] Trend prediction for computer science research topics using extreme learning machine

N Sari, A Widodo - Procedia Engineering, 2012 - Elsevier