Computational Intelligence in Automotive Applications Episode 2 Part 5 pdf
Computational Intelligence in Automotive Applications Episode 2 Part 5 pdf
... Welding,
Proceedings of 20 06 IEEE World Congress of Computational Intelligence, 20 06 IEEE International Conference
on Fuzzy Systems, Vancouver, 157 0– 157 7, 20 06.
16. D. Dickinson, J. Franklin, ... with
∗
Corresponding author, roger.bostelman@nist.gov
J. Albus et al.: Intelligent Control of Mobility Systems, Studies in Computational Intelligence (SCI) 1 32, 23 7 27 4 (20 08)...
Computational Intelligence in Automotive Applications Episode 2 Part 1 docx
... (Case 1)
5 5 .5 6 6 .5 7 7 .5 8
12
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Time [s]
measured
predicted
5 5 .5 6 6 .5 7 7 .5 8
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20
Time [s]
AFR [/] - (Case 2)
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Time ... 6 .5 7 7 .5 8
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Time [s]
AFR [/] (Case 3)
5 5 .5 6 6 .5 7 7 .5 8
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18
19
20
2...
Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt
... ramps 34.6 60 .2 5. 7 26 6
Arterials LOS A–B 24 .8 58 .9 5. 0 737
Arterials LOS C–D 19 .2 49 .5 5.7 629
Arterials LOS E–F 11.6 39.9 5. 8 50 4
Local roadways 12. 9 38.3 3.7 52 5
• Normal driving implies moderate ... rad/s
314 rad/s
26 1 rad/s
104 rad/s
157 rad/s
20 9 rad/s
(a) engine efficiency map
0 0 .5 1 1 .5 2 2 .5
0
0 .5
1
1 .5
2
2 .5
Mechanical Power[kW ]
Electr...
Computational Intelligence in Automotive Applications Episode 2 Part 3 ppsx
... models in order to be effective.
K. Pattipati et al.: An Integrated Diagnostic Process for Automotive Systems, Studies in Computational Intelligence (SCI) 1 32,
191 21 8 (20 08)
www.springerlink.com
c
... observer [ 52 ] , Kalman filters and Interacting Multiple Models [1], output observers [43, 54 ],
nonlinear observers [20 , 53 ], to name a few.
An Integrated Diagnostic Process...
Computational Intelligence in Automotive Applications Episode 2 Part 4 pptx
... Parameter
Estimation
R
w
K
f
I
w
τ
m
K
f
err 3 . 25 .06. 0 25 .01. 05
std 1 .23 .56 . 822 .20 . 12
I
w
err 2. 04 .54 .019.00. 52
std 1.64.87 .23 9.30. 35
τ
m
err 3 .57 .810. 327 . 52 . 0
std 2. 45 . 25 .646 .50 .80
R
w
err 0.39 0.33 2. 98 27 9.33 0.004
std 0 . 25 0. 12 1.48 ... fault (F8) +36. 32 +0.40 2. 01 2. 90 26 .28 −0.16
Engine speed sensor fault (F9) −7.14 +10.46 25 .19 26...
Computational Intelligence in Automotive Applications Episode 2 Part 6 doc
... Distance
2
Pos
it
i
on
Obje
c
t-I
D
O
ffs
et
Pas
s
Spe
ed
Fol
lo
w
in
gDi
s
t
Costs to Vio
l
ate
X-80934
Y -23 8 82
Z -23 457
X-8093
Y -23 8 82
X-80934
X-80934
X-80934
Y -23 8 82
Z -23 457
Objects-of-Interest
Table
Fig. ... referenced in various public docu-
ments, including the ASTM Standards E2 52 1 -07, F 23 95- 05, and F 25 41-06 for various UMSs as well as the
U.S. Army UNMA...
Computational Intelligence in Automotive Applications Episode 2 Part 7 potx
... 25 6, 25 9, 26 1, 27 1
Lane tracking, 36
Learning Applied to Ground Robots (LAGR), 23 8, 25 5
Learning machines, 1 25
Learning rate, 114
Learning vector quantization (LVQ), 1 85, 22 0, 22 3 22 6,
22 8, 23 4
Learning-based ... System
(4D/RCS), 23 7
Fuzzy logic, 174, 1 75, 22 0, 22 7, 22 9, 23 4
27 6 Index
Fuzzy rules, 174, 1 75, 180, 1 82, 22 9, 23 0
Fuzzy system, 22 , 2...
Computational Intelligence in Automotive Applications Episode 1 Part 5 docx
... Computer Vision and Machine Learning for Enhancing Pedestrian Safety 69
0 1 2 3 4 5
0 .5
1
1 .5
2
2 .5
3
3 .5
4
4 .5
decision boundary
2 −1 0 1 2
2
−1 .5
−1
−0 .5
0
0 .5
1
1 .5
2
(a)
(b)
Fig. 8. Illustration ... Machine Intelligence, pp. 918– 923 , July 20 03.
31. D.V. Prokhorov. Neural Networks in Automotive Applications. Computational Intelligence in Auto...
Computational Intelligence in Automotive Applications Episode 1 Part 2 pdf
... F09-F10) 32 70
Pupil-diameter features only (F09-F10) 2 61
Driving-performance features (F01-F08) 8 60
PleaserefertoTable2forthefeatureindices
0
2
4
6
8
10
12
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
Feature ... 1 /5: (11 .5/ 1 .5, lift 2. 1)
F01 > 2. 4 056
F21 <= 0.06 35
-> class High [0.8 12]
Rule 1/6: (21 .4/3.8, lift 2. 0)
F09 <= 21 .24 43
-&...
Computational Intelligence in Automotive Applications Episode 1 Part 1 pptx
... 481 05
USA
dvprokhorov@gmail.com
ISBN 978-3 -54 0-7 9 25 6-7 e-ISBN 978-3 -54 0-7 9 25 7-4
Studies in Computational Intelligence ISSN 1860-949X
Library of Congress Control Number: 20 08 9 25 55 4
c
20 08 Springer-Verlag ... 119
On Learning Machines for Engine Control
G´erard Bloch, Fabien Lauer, and Guillaume Colin 1 25
1 Introduction 1 25
1.1 CommonFeaturesin EngineControl 1 25...
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