MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02089nam a22002537a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
ZW-GwMSU |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240604140406.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240604b |||||||| |||| 00| 0 eng d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| International Standard Serial Number |
01446193 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MSU |
| Language of cataloging |
English |
| Transcribing agency |
MSU |
| Description conventions |
rda |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
HD9715.A1 CON |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Goh, Yang Miang |
| Relator term |
author |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Neural network analysis of construction safety management systems: |
| Remainder of title |
a case study in Singapore |
| Statement of responsibility, etc. |
created by Yang Miang Goh and David Chua |
| 264 1# - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Abingdon: |
| Name of producer, publisher, distributor, manufacturer |
Taylor and Francis, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2013 |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| Carrier type code |
nc |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Construction Management and Economics |
| Volume/sequential designation |
Volume 31, number 4-6 |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
A neural network analysis was conducted on a quantitative occupational safety and health management system (OSHMS) audit with accident data obtained from the Singapore construction industry. The analysis is meant to investigate, through a case study, how neural network methodology can be used to understand the relationship between OSHMS elements and safety performance, and identify the critical OSHMS elements that have significant influence on the occurrence and severity of accidents in Singapore. Based on the analysis, the model may be used to predict the severity of accidents with adequate accuracy. More importantly, it was identified that the three most significant OSHMS elements in the case study are: incident investigation and analysis, emergency preparedness, and group meetings. The findings imply that learning from incidents, having well-prepared consequence mitigation strategies and open communication can reduce the severity and likelihood of accidents on construction worksites in Singapore. It was also demonstrated that a neural network approach is feasible for analysing empirical OSHMS data to derive meaningful insights on how to improve safety performance |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Accident |
| Form subdivision |
Management system |
| General subdivision |
Neural network |
| Geographic subdivision |
Singapore |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Chua, David |
| Relator term |
co-author |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
https://doi.org/10.1080/01446193.2013.797095 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Journal Article |