PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Comparison Between Tailor-Made-ANN Techniques and Fuzzy c-Mean Clustering Technique in Industrial Laborers' Accident-Rates Prediction Modelling Based on Human Factors
Version 1
: Received: 30 June 2021 / Approved: 1 July 2021 / Online: 1 July 2021 (11:17:53 CEST)
How to cite:
M.A.S. Mahmoud, M. Comparison Between Tailor-Made-ANN Techniques and Fuzzy c-Mean Clustering Technique in Industrial Laborers' Accident-Rates Prediction Modelling Based on Human Factors. Preprints2021, 2021070016. https://doi.org/10.20944/preprints202107.0016.v1
M.A.S. Mahmoud, M. Comparison Between Tailor-Made-ANN Techniques and Fuzzy c-Mean Clustering Technique in Industrial Laborers' Accident-Rates Prediction Modelling Based on Human Factors. Preprints 2021, 2021070016. https://doi.org/10.20944/preprints202107.0016.v1
M.A.S. Mahmoud, M. Comparison Between Tailor-Made-ANN Techniques and Fuzzy c-Mean Clustering Technique in Industrial Laborers' Accident-Rates Prediction Modelling Based on Human Factors. Preprints2021, 2021070016. https://doi.org/10.20944/preprints202107.0016.v1
APA Style
M.A.S. Mahmoud, M. (2021). Comparison Between Tailor-Made-ANN Techniques and Fuzzy c-Mean Clustering Technique in Industrial Laborers' Accident-Rates Prediction Modelling Based on Human Factors. Preprints. https://doi.org/10.20944/preprints202107.0016.v1
Chicago/Turabian Style
M.A.S. Mahmoud, M. 2021 "Comparison Between Tailor-Made-ANN Techniques and Fuzzy c-Mean Clustering Technique in Industrial Laborers' Accident-Rates Prediction Modelling Based on Human Factors" Preprints. https://doi.org/10.20944/preprints202107.0016.v1
Abstract
This paper attempts to compare two different approaches to solve the problem of accident rates prediction based on human factors for industrial workers. One of the methods has already been done using Fuzzy c-Means Clustering and proved to be working with decent results. The second method which will be covered in this paper is using Artificial Neural Networks. The primary goal of this work is to insure that ANN will work efficiently in such prediction problem. The second goal is to reveal the fact that which one of the two selected methodologies is better at defining the estimation of accident rates among people who work in different industrial fields. The purpose has been achieved when the outcome of the ANN was obtained and compared accordingly with the output of the research previously carried out with Fuzzy c-means clustering method. Comparing the outcomes of these two different methods gave an immense insight on which features are more important than others when it comes to laborers properties with completely different background such as varying levels of health, knowledge, experience, training and physical properties. At the end of the research, it becomes clear that accident rates estimation for laborers with properly trained Artificial Neural Network gives better results when it is compared with Fuzzy c-Means Clustering method. Standard deviation method was used to calculate the validity of ANN technique. The result was compared with Fuzzy c-mean clustering technique. Impressive improvement of 8.8% in the accident rate prediction was achieved using Tailored-Made-ANN.
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
