Librarian View
LEADER
03444cam a2200601 a 4500
001
9143416
005
20110222095359.0
006
m d f
007
cr gn|||||||||
008
080513s2007 dcu sb f000 0 eng c
029
0
|a
DTICE
|b
ADA471597
035
|a
(OCoLC)ocn227949976
040
|a
DTICE
|c
DTICE
|d
GPO
|d
MvI
042
|a
pcc
043
|a
n-us---
049
|a
yuli
074
|a
0431-E-04 (online)
088
|a
DOT/FAA/AM-07/18
086
0
|a
TD 4.210:07/18
100
1
|a
Pfleiderer, Elaine M.
245
1
0
|a
Prediction and classification of operational errors and routine operations using sector characteristics variables
|h
[electronic resource] /
|c
Elaine M. Pfleiderer, Carol A. Manning.
260
|a
Washington, DC :
|b
Federal Aviation Administration, Office of Aerospace Medicine,
|c
[2007]
300
|a
1 online resource (v, 11 p.)
513
|a
Final report.
500
|a
Title from title screen (viewed Jan. 5, 2010).
500
|a
"July 2007."
504
|a
Includes bibliographical references (p. 10-11).
520
|a
This study examined prediction and classification of operational errors (OEs) and routine operations (ROs) using sector characteristics variables. Average Control Duration, Aircraft Mix Index, Average Lateral Distance, Average Vertical Distance, Number of Handoffs, Number of Point Outs, Number of Transitioning Aircraft, and Number of Heading Changes were used as predictors in two stepwise logistic regression analyses conducted for the high-altitude and low-altitude sectors. In the high-altitude sample, variables included in the final model (Number of Heading Changes, Number of Transitioning Aircraft, and Average Control Duration) accurately classified OE and RO samples for 80% of the cases. In the low-altitude sample, variables included in the final model (Number of Point Outs, the Number of Handoffs, and the Number of Heading Changes) accurately classified OE and RO samples for 79% of the cases. Although logistic regression cannot be used to determine causation, it effectively identified variables that predicted the occurrence of OEs.
500
|a
"DOT/FAA/AM-07/18."
536
|g
AM-B07-HRR-522
650
0
|a
Air traffic control
|z
United States
|x
Safety measures
|x
Statistical methods.
650
0
|a
Airports
|z
United States
|x
Traffic control
|x
Safety measures
|x
Statistical methods.
650
0
|a
Logistic regression analysis.
650
1
7
|a
Air Navigation and Guidance.
|2
scgdst
650
1
7
|a
Air traffic control systems.
|2
dtict
650
2
7
|a
Predictions.
|2
dtict
650
2
7
|a
Regression analysis.
|2
dtict
650
2
7
|a
Error analysis.
|2
dtict
650
2
7
|a
Classification.
|2
dtict
650
2
7
|a
Logistics.
|2
dtict
653
2
|a
SECTOR CHARACTERISTICS
653
2
|a
COMPLEXITY
653
2
|a
OE(OPERATIONAL ERRORS)
653
2
|a
LOGISTIC REGRESSION ANALYSIS
653
2
|a
ROS(ROUTINE OPERATIONS)
776
0
8
|i
Print version:
|a
Pfleiderer, Elaine M.
|t
Prediction and classification of operational errors and routine operations using sector characteristics variables
|h
v, 11 p.
|w
(OCoLC)166587237
700
1
|a
Manning, Carol A.
|q
(Carol Ann),
|d
1954-
710
1
|a
United States.
|b
Office of Aerospace Medicine.
852
8
0
|z
Online Resource
856
4
0
|u
http://purl.access.gpo.gov/GPO/LPS118290
902
|a
Yale Internet Resource
|b
Yale Internet Resource >> None|DELIM|9511668
905
|a
online resource
907
|a
2010-02-08T12:28:59.000Z