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...
Ngày tải lên: 07/08/2014, 09:23
... Machine Intelligence, pp. 918 –923, July 2003. 31. D.V. Prokhorov. Neural Networks in Automotive Applications. Computational Intelligence in Automotive Applications, Studies in Computational Intelligence, ... they are related by 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 3...
Ngày tải lên: 07/08/2014, 09:23
... 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 0.85 Tool in (2 ,4) 240 0. 81 Tool in (1, 4) 244 0. 81 Location in ... constrain the manufacturing process to a particular subset of in uence variables. Neural Networks in Automotive Applications 10 5 1. 5 1. 6 1. 7...
Ngày tải lên: 07/08/2014, 09:23
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 ... and Marco Sorrentino 14 5 1 Introduction 14 5 2 Manifold FuelFilmDynamics 14 6 3 AFR Control 14 8 3 .1 RNN Potential 14 9 4 RecurrentNeural Networks...
Ngày tải lên: 07/08/2014, 09:23
Computational Intelligence in Automotive Applications Episode 1 Part 2 pdf
... lift 1. 2) F09 > 21. 244 3 F15 > 0.0056 F15 <= 0. 017 4 F 21 > 0.0635 -> class Low [0.979] Rule 1/ 10: (92 .1/ 1.5, lift 1. 2) F 01 > -1. 563 F08 > 0.0 243 F09 > 21. 244 3 ... [0.828] Rule 1/ 5: (11 .5 /1. 5, lift 2 .1) F 01 > 2 .40 56 F 21 <= 0.0635 -> class High [0. 812 ] Rule 1/ 6: ( 21. 4/ 3.8, lift 2.0) F09 <= 21. 244 3...
Ngày tải lên: 07/08/2014, 09:23
Computational Intelligence in Automotive Applications Episode 1 Part 3 ppt
... (s) 1 3 94 (two intervals: 18 0 + 2 14 ) 516 910 2 90 (one interval) 210 300 3 0 240 240 4 15 5 (one interval) 17 5 330 5 16 0 (one interval) 393 553 6 18 0 (one interval) 370 550 7 310 (two intervals: 15 0 ... 310 (two intervals: 15 0 + 16 0) 6 31 9 41 8 842 (two intervals: 390 + 45 2) 765 1, 607 9 210 (two intervals: 75 + 13 5) 255 46 5 10 673 (two intervals: 310 + 363...
Ngày tải lên: 07/08/2014, 09:23
Computational Intelligence in Automotive Applications Episode 1 Part 7 pptx
... Automotive Applications 11 7 0 50 10 0 15 0 200 250 300 350 40 0 1 −0.5 0 0.5 1 0 50 10 0 15 0 200 250 300 350 40 0 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-Ver...
Ngày tải lên: 07/08/2014, 09:23
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 4 pptx
... 2 67.7 10 0.030.7 Slope 3 73.990 . 14 5.8 Slope 4 10 0.037 .49 9.8 Bin 1 83.6 31. 376.2 Bin 2 90. 716 .088.7 Bin 3 89. 6 14 .5 10 0.0 Bin 4 92 .1 100. 0 14 .4 Bin 5 98 .12 0.698.6 In order to reduce the dimensionality ... 2. 512 .8 ± 2 .11 4 .1 ± 2 .12 1 .1 ± 3.733 .1 ± 3. 216 .3 ± 2.3 data via classification MPLS Tandem (serial) 15 .87 ± 2 .49 (12 .8 KB) fusion Fusion cen...
Ngày tải lên: 07/08/2014, 09:23
Computational Intelligence in Automotive Applications Episode 2 Part 6 doc
... Objects-of-Interest table to generate a set of goal paths for the vehicle that meets the control values specified in the table. GP 113 GP 1 14 GP 115 GP 116 GP 117 Vehicle’s Goal Paths - Fig. 14 . Elemental ... al. 2 Dynamic Trajectories built from Goal Paths. GP 113 GP 1 14 GP 117 GP 116 GP 115 Fig. 15 . Primitive/Trajectory control module pre-calculates (at 10 0× real-time) t...
Ngày tải lên: 07/08/2014, 09:23