Computational Intelligence in Automotive Applications Episode 2 Part 7 potx

Computational Intelligence in Automotive Applications Episode 1 Part 1 pptx

Computational Intelligence in Automotive Applications Episode 1 Part 1 pptx

... Networks in Automotive Applications Danil Prokhorov 10 1 1 Models 10 1 2 VirtualSensors 10 3 3 Controllers 10 6 4 TrainingNN 11 1 5 RNN: AMotivatingExample 11 6 6 VerificationandValidation (V &V) 11 8 References ... 11 8 References 11 9 On Learning Machines for Engine Control G´erard Bloch, Fabien Lauer, and Guillaume Colin 12 5 1 Introduction 12 5 1. 1 CommonFeatures...

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Computational Intelligence in Automotive Applications Episode 1 Part 2 pdf

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 (F 01- 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 ... the features 12 Y. Zhang et al. Rule 1/ 1: ( 41. 4/4.6, lift 2. 2) F10 > 3. 526 F 21 <= 0.0635 -> class High [0.8 71] Rule 1/ 2:...

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Computational Intelligence in Automotive Applications Episode 1 Part 3 ppt

Computational Intelligence in Automotive Applications Episode 1 Part 3 ppt

... (s) 1 39 4 (two intervals: 18 0 + 214 ) 516 910 2 90 (one interval) 210 30 0 3 0 240 240 4 15 5 (one interval) 17 5 33 0 5 16 0 (one interval) 39 3 5 53 6 18 0 (one interval) 37 0 550 7 31 0 (two intervals: 15 0 ... 550 7 31 0 (two intervals: 15 0 + 16 0) 6 31 9 41 8 842 (two intervals: 39 0 + 452) 765 1, 607 9 210 (two intervals: 75 + 13 5) 255 465 10 6 73 (two inte...

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Computational Intelligence in Automotive Applications Episode 1 Part 4 doc

Computational Intelligence in Automotive Applications Episode 1 Part 4 doc

... controls 74% Eating a meal/snack 51% Using a cell phone 41 % Tending to children 34% Reading a map/publication 19 % Grooming 11 % Prepared for work Activities drivers engage in while driving each. ... transcriptions in real time. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP88), pp. 611 – 6 14 , New York City, USA, April 11...

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Computational Intelligence in Automotive Applications Episode 1 Part 5 docx

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 2003. 31. D.V. Prokhorov. Neural Networks in Automotive Applications. Computational Intelligence in Automo...

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Computational Intelligence in Automotive Applications Episode 1 Part 6 doc

Computational Intelligence in Automotive Applications Episode 1 Part 6 doc

... Location 6. 0092 1 1 Right 6. 008 4 2 Right 6. 00 61 4 2 Right 6. 0 067 1 2 Left 6. 00 76 4 1 Right 6. 0082 2 2 Left 6. 0075 3 1 Right 6. 0077 3 2 Right 6. 00 61 2 1 Left 6. 0 063 1 1 Right 6. 0 063 1 2 Right improve ... Tool in (4) 18 2 0. 81 Tool not in (4) and shaft in (2) 18 3 0. 81 Tool not in (1) and location in (right) 210 0.84 Tool in (1,...

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Computational Intelligence in Automotive Applications Episode 1 Part 7 pptx

Computational Intelligence in Automotive Applications Episode 1 Part 7 pptx

... Automotive Applications 11 7 0 50 10 0 15 0 200 250 300 350 400 1 −0.5 0 0.5 1 0 50 10 0 15 0 200 250 300 350 400 1 −0.5 0 0.5 1 Testing Training Fig. 11 . The RNN results after training. The segment from ... 19 97, pp. 77 3 77 8. 75 . D. Prokhorov, “Toward effective combination of off-line and on-line training in ADP framework,” in Proceedings of the 20 07 IEEE Symp...

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Computational Intelligence in Automotive Applications Episode 1 Part 8 potx

Computational Intelligence in Automotive Applications Episode 1 Part 8 potx

... 0 .8 1 0 10 20 30 0.4 0.6 0 .8 1 0 10 20 30 0.4 0.6 0 .8 1 0 10 20 30 0.4 0.6 0 .8 1 0 10 20 30 0.4 0.6 0 .8 1 0 10 20 30 0.4 0.6 0 .8 1 0 10 20 30 N e = 10 00 rp m OF =0 ◦ CA/m OF =0. 41 ◦ CA/m OF =1. 16 ◦ CA/m N e = ... and Control in Spark Ignition Automotive Engines, Studies in Computational Intelligence (SCI) 13 2, 14 5 16 8 (20 08) www.spri...

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Computational Intelligence in Automotive Applications Episode 2 Part 1 docx

Computational Intelligence in Automotive Applications Episode 2 Part 1 docx

... 2) 5 5.5 6 6.5 7 7.5 8 12 13 14 15 16 17 18 19 20 Time [s] AFR [/] (Case 3) 5 5.5 6 6.5 7 7.5 8 12 13 14 15 16 17 18 19 20 21 Time [s] AFR [/] (Case 4) 5 5.5 6 6.5 7 7.5 8 12 13 14 15 16 17 18 19 20 Time ... - (Case 2) 5 5.5 6 6.5 7 7.5 8 12 13 14 15 16 17 18 19 20 Time [s] AFR [/] (Case 3) 5 5.5 6 6.5 7 7.5 8 12 13 14 15 16 17 18...

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Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt

Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt

... Murphey: Intelligent Vehicle Power Management: An Overview, Studies in Computational Intelligence (SCI) 1 32, 169–190 (20 08) www.springerlink.com c  Springer-Verlag Berlin Heidelberg 20 08 Intelligent ... important and challenging problem. 1 Introduction Automotive industry is facing increased challenges of producing affordable vehicles with increased electri- cal/electronic compon...

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Computational Intelligence in Automotive Applications Episode 2 Part 3 ppsx

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  ... system by inte- grating the individual diagnostic elements of design for testability, on-board diagnostics, automatic testing, manual troubleshooting, training, maintenance aidi...

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Computational Intelligence in Automotive Applications Episode 2 Part 4 pptx

Computational Intelligence in Automotive Applications Episode 2 Part 4 pptx

... 3 .25 .06. 025 .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 0.0 04 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 .23 −1.55 −3.08 Overall % of error 21 .60 −1.09 2...

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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)...

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Computational Intelligence in Automotive Applications Episode 2 Part 6 doc

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 521 -07, F 23 95-05, and F 25 41- 06 for various UMSs as well as the U.S. Army UNMANN...

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Computational Intelligence in Automotive Applications Episode 2 Part 7 potx

Computational Intelligence in Automotive Applications Episode 2 Part 7 potx

... 191 Fixed gaze, 26 , 28 –30, 32, 36 Four Dimensional (3D+ time)/Real-time Control System (4D/RCS), 23 7 Fuzzy logic, 174 , 175 , 22 0, 22 7, 22 9, 23 4 27 6 Index Fuzzy rules, 174 , 175 , 180, 1 82, 22 9, 23 0 Fuzzy ... profile, 22 3, 22 4, 22 6, 22 7, 23 4 Embodied agent, 26 7 Engine actuators, 125 control, 125 , 131 common features, 125 development cycle, 1 27 downs...

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