Computational Intelligence in Automotive Applications Episode 2 Part 4 pptx

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 1 docx

Computational Intelligence in Automotive Applications Episode 2 Part 1 docx

... Control 44 : 22 00 22 05. 12. Dovifaaz X, Ouladsine M, Rachid A (1999) Optimal control of a turbocharged diesel engine using neural network. In: 14th IFAC World Congress, IFAC-8b-009, Beijing, China, ... control applications [10, 24 , 32, 42 ] and the accomplishment of this task isdescribedinSect.6.1. 6.1 Training and Test Data The training and test sets were generated by running the e...

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Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt

Computational Intelligence in Automotive Applications Episode 2 Part 2 ppt

... 67.79 79. 52 2.3 399 Freeway LOS B 66.91 78. 34 2. 9 366 Freeway LOS C 66. 54 78. 74 3 .4 448 Freeway LOS D 65 .25 77.56 2. 9 43 3 Freeway LOS E 57 .2 74. 43 4. 0 47 1 Freeway LOS F 32. 63 63.85 4. 0 536 Freeway ... Murphey: Intelligent Vehicle Power Management: An Overview, Studies in Computational Intelligence (SCI) 1 32, 169–190 (20 08) www.springerlink.com c  Springer-...

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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 aidin...

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Computational Intelligence in Automotive Applications Episode 2 Part 5 pdf

Computational Intelligence in Automotive Applications Episode 2 Part 5 pdf

... 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) www.springerlink.com c  Springer-Verlag ... cold welds in the fuzzy control scheme test (31 /21 6 = 14. 4%) was less than the number of cold welds in the stepper mode (44 /21 6 = 20 .4% ). 4 .2 Int...

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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-809 34 Y -23 8 82 Z -23 45 7 X-8093 Y -23 8 82 X-809 34 X-809 34 X-809 34 Y -23 8 82 Z -23 45 7 Objects-of-Interest Table Fig. ... attributes maps cost objects terrain 20 0x200 pix 40 0x400 m frames names attributes state class relations WM2 Manage KD2 maps cost objects terrain...

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Computational Intelligence in Automotive Applications Episode 2 Part 7 potx

Computational Intelligence in Automotive Applications Episode 2 Part 7 potx

... System (4D/RCS), 23 7 Fuzzy logic, 1 74, 175, 22 0, 22 7, 22 9, 23 4 27 6 Index Fuzzy rules, 1 74, 175, 180, 1 82, 22 9, 23 0 Fuzzy system, 22 , 29 Graphical models, 79, 80, 88 Grey box approach, 127 Hardware -in- the-loop, ... activity, 39, 42 , 56 Dynamic fusion, 21 0 Dynamic Programming, 169, 171, 1 74, 176, 188 Dynamic resistance approach, 22 2 Dynamic resistance profile,...

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Computational Intelligence in Automotive Applications Episode 1 Part 1 pptx

Computational Intelligence in Automotive Applications Episode 1 Part 1 pptx

... Schlenoff, Hui-Min Huang, and Fred Proctor 23 7 1 Introduction 23 7 2 Autonomous On-RoadDriving 23 9 2. 1 NIST HMMWVTestbed 23 9 2. 2 4D/RCSTaskDecomposition ControllerforOn-Road Driving 24 1 2. 3 LearningApplied ... oftheDatabase 42 4 Driving Data Classification 43 4. 1 DecisionTrees 44 4 .2 RandomForests 45 4. 3 RandomForestsforDriving ManeuverDetection 46 5 SensorSele...

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Computational Intelligence in Automotive Applications Episode 1 Part 4 doc

Computational Intelligence in Automotive Applications Episode 1 Part 4 doc

... performance. In Proceedings of NIPS, pp. 196 20 2, 20 00. 4. L. Breiman. Bagging predictors. Machine Learning, 24 (2) : 123 – 140 , 1996. 5. L. Breiman. Random forests. Machine Learning, 45 (1):5– 32, 20 01. 6. ... an index of workload. In Proceedings of the IEA/HFES 20 00 Congress, pp. 125 – 128 , 20 00. 2. E.R. Boer. Behavioral entropy as a measure of driving performance. In...

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Computational Intelligence in Automotive Applications Episode 1 Part 7 pptx

Computational Intelligence in Automotive Applications Episode 1 Part 7 pptx

... Bloch et al.: On Learning Machines for Engine Control, Studies in Computational Intelligence (SCI) 1 32, 125 – 144 (20 08) www.springerlink.com c  Springer-Verlag Berlin Heidelberg 20 08 116 D. Prokhorov transformation ... Miller, “An in- vehicle virtual driving assistant using neural networks,” in Proceedings of the International Joint Conference on Neural Networks (IJCNN), vol. 3...

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