東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Quantifying the impact of constructi...

Schmidt, John R.

FindBook

Google Book

Amazon

博客來

Quantifying the impact of construction accidents using predictive models.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Quantifying the impact of construction accidents using predictive models./
作者:	Schmidt, John R.
面頁冊數:	132 p.
附註:	Source: Dissertation Abstracts International, Volume: 58-01, Section: B, page: 0323.
Contained By:	Dissertation Abstracts International58-01B.
標題:	Health Sciences, Occupational Health and Safety. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9719173
ISBN:	9780591275766

Quantifying the impact of construction accidents using predictive models.
Schmidt, John R.

Quantifying the impact of construction accidents using predictive models. - 132 p.

Source: Dissertation Abstracts International, Volume: 58-01, Section: B, page: 0323.

Thesis (Ph.D.)--State University of New York at Buffalo, 1997.

A simple method for a contractor to predict the impact of construction accidents does not currently exist. This research looks at the efficacy of statistical modeling of construction safety data, investigates methods to model construction safety performance, and presents tools to predict the impacts of accident losses in compensation weeks. This is done for a given source and nature of injury or illness, accident type, disability type, occupation, part of body involved, and age of injured. The results of this research have demonstrated the efficacy of a few modeling approaches, exposing the potential for continued research and refinement to suit the user industry. The New York State Workers' Compensation data of 91,953 cases of construction injuries and illnesses closed between 1980 to 1988 serve as the basis for this research. Linear regression modeling is investigated and suggestions for improvement of such a model are presented. The introduction of classification and regression trees (CART) as a tool for simplified analyses of the impact of construction-related accidents is presented. The concepts for the models developed herein can be used to predict the impact of construction work site accident losses in compensation weeks. Refined versions of these regression and CART models may prove useful to many in the construction industry including insurance providers, contractors, safety professionals, construction engineers, construction managers, and design engineers.

ISBN: 9780591275766Subjects--Topical Terms:

1017799
Health Sciences, Occupational Health and Safety.

Quantifying the impact of construction accidents using predictive models.
LDR:02428nmm 2200301 4500 001 1829784
005 20070216133626.5
008 130610s1997 eng d
020 $a 9780591275766
035 $a (UnM)AAI9719173
035 $a AAI9719173
040 $a UnM $c UnM
100 1 $a Schmidt, John R. $3 1918636
245 1 0 $a Quantifying the impact of construction accidents using predictive models.
300 $a 132 p.
500 $a Source: Dissertation Abstracts International, Volume: 58-01, Section: B, page: 0323.
500 $a Adviser: Satish Mohan.
502 $a Thesis (Ph.D.)--State University of New York at Buffalo, 1997.
520 $a A simple method for a contractor to predict the impact of construction accidents does not currently exist. This research looks at the efficacy of statistical modeling of construction safety data, investigates methods to model construction safety performance, and presents tools to predict the impacts of accident losses in compensation weeks. This is done for a given source and nature of injury or illness, accident type, disability type, occupation, part of body involved, and age of injured. The results of this research have demonstrated the efficacy of a few modeling approaches, exposing the potential for continued research and refinement to suit the user industry. The New York State Workers' Compensation data of 91,953 cases of construction injuries and illnesses closed between 1980 to 1988 serve as the basis for this research. Linear regression modeling is investigated and suggestions for improvement of such a model are presented. The introduction of classification and regression trees (CART) as a tool for simplified analyses of the impact of construction-related accidents is presented. The concepts for the models developed herein can be used to predict the impact of construction work site accident losses in compensation weeks. Refined versions of these regression and CART models may prove useful to many in the construction industry including insurance providers, contractors, safety professionals, construction engineers, construction managers, and design engineers.
590 $a School code: 0656.
650 4 $a Health Sciences, Occupational Health and Safety. $3 1017799
650 4 $a Engineering, Industrial. $3 626639
650 4 $a Engineering, General. $3 1020744
650 4 $a Engineering, Civil. $3 783781
690 $a 0543
690 $a 0354
690 $a 0546
690 $a 0537
710 2 0 $a State University of New York at Buffalo. $3 1017814
773 0 $t Dissertation Abstracts International $g 58-01B.
790 1 0 $a Mohan, Satish, $e advisor
790 $a 0656
791 $a Ph.D.
792 $a 1997
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9719173