Computational Intelligence in Automotive Applications Episode 1 Part 3 ppt

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 7 pptx

Computational Intelligence in Automotive Applications Episode 1 Part 7 pptx

... Automotive Applications 11 7 0 50 10 0 15 0 200 250 30 0 35 0 400 1 −0.5 0 0.5 1 0 50 10 0 15 0 200 250 30 0 35 0 400 1 −0.5 0 0.5 1 Testing Training Fig. 11 . The RNN results after training. The segment from ... et al.: On Learning Machines for Engine Control, Studies in Computational Intelligence (SCI) 13 2, 12 5 14 4 (2008) www.springerlink.com c  Springer-Ve...

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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 CommonFeatur...

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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 ... F09 > 21. 24 43 F15 <= 0. 017 4 F 21 > 0.0 635 -> class Low [0.9 73] Rule 1/ 11: ( 31 . 6, lift 1. 2) F 01 > 0 .30 84 F 01...

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Computational Intelligence in Automotive Applications Episode 1 Part 4 doc

Computational Intelligence in Automotive Applications Episode 1 Part 4 doc

... as: ⎛ ⎝ X b Y b Z b ⎞ ⎠ = λ ⎛ ⎝ h 11 h 12 h 13 h 21 h 32 h 33 h 31 h 32 1 ⎞ ⎠ ⎛ ⎝ X a Y a Z a ⎞ ⎠ (4) The perspective camera coordinates can be mapped to pixel coordinates (u a ,v a )and(u b ,v b )usingthe internal calibration ... Joint Conference on Artificial Intel ligence, Montreal, Canada, 19 95. 11 . I. Guyon and A. Elisseeff. An introduction to feature selection. Jour...

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Computational Intelligence in Automotive Applications Episode 1 Part 5 docx

Computational Intelligence in Automotive Applications Episode 1 Part 5 docx

... the following equations: u 2 = h 11 u 1 + h 12 v 1 + h 13 h 31 u 1 + h 32 v 1 + h 33 ,v 2 = h 21 u 1 + h 22 v 1 + h 23 h 31 u 1 + h 32 v 1 + h 33 (17 ) The matrix H formed from elements h ij is the ... Machine Intelligence, pp. 918 –9 23, July 20 03. 31 . D.V. Prokhorov. Neural Networks in Automotive Applications. Computational Intelligence...

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Computational Intelligence in Automotive Applications Episode 1 Part 6 doc

Computational Intelligence in Automotive Applications Episode 1 Part 6 doc

... X 0 12 3 0.85 Tool in (2,4) and location in (left) 12 6 0.86 Shaft in (2) and location in (right) 12 7 0. 83 Tool in (2 ,3) and shaft in (2) 13 0 0. 83 Tool in (1, 4) and location in (right) 13 3 0. 83 Tool ... 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, 2) 236...

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Computational Intelligence in Automotive Applications Episode 1 Part 8 potx

Computational Intelligence in Automotive Applications Episode 1 Part 8 potx

... =3. 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 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 ... and Control in Spark Ignition Automotive Engines, Studies in Computational Intelligence (SCI) 13 2, 14 5 16 8 (2008) www.springerlink.co...

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Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt

Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt

... 2 .3 399 Freeway LOS B 66. 91 78 .34 2.9 36 6 Freeway LOS C 66.54 78.74 3. 4 448 Freeway LOS D 65.25 77.56 2.9 433 Freeway LOS E 57.2 74. 43 4.0 4 71 Freeway LOS F 32 . 63 63. 85 4.0 536 Freeway ramps 34 .6 ... Murphey: Intelligent Vehicle Power Management: An Overview, Studies in Computational Intelligence (SCI) 13 2, 16 9 19 0 (2008) www.springerlink.com c  Springer-Verl...

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Computational Intelligence in Automotive Applications Episode 2 Part 3 ppsx

Computational Intelligence in Automotive Applications Episode 2 Part 3 ppsx

... engine system Fault\test R1 R2 hR2lR3R4R5R6hR6l F0 0 0 0 0 0 0 0 0 F1 0 1 0 0 0 0 0 0 F2 0 0 1 1 0 0 1 0 F3 0 0 1 1 0 0 0 1 F4 0 0 0 1 0 0 0 1 F5 1 0 0 0 0 0 0 0 F6 0 0 0 1 1 1 1 0 F7 0 0 0 1 ... models in order to be effective. K. Pattipati et al.: An Integrated Diagnostic Process for Automotive Systems, Studies in Computational Intelligence (SCI) 13 2, 19 1–...

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