000 04273nam a22005055i 4500
001 978-3-540-79257-4
003 DE-He213
005 20161121230549.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 _a9783540792574
_9978-3-540-79257-4
024 7 _a10.1007/978-3-540-79257-4
_2doi
050 4 _aTL1-483
072 7 _aTRC
_2bicssc
072 7 _aTRCS
_2bicssc
072 7 _aTEC009090
_2bisacsh
082 0 4 _a629.2
_223
245 1 0 _aComputational Intelligence in Automotive Applications
_h[electronic resource] /
_cedited by Danil Prokhorov.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2008.
300 _aXV, 365 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v132
505 0 _aLearning-Based Driver Workload Estimation -- Visual Monitoring of Driver Inattention -- Understanding Driving Activity Using Ensemble Methods -- Computer Vision and Machine Learning for Enhancing Pedestrian Safety -- Application of Graphical Models in the Automotive Industry -- Extraction of Maximum Support Rules for the Root Cause Analysis -- Neural Networks in Automotive Applications -- On Learning Machines for Engine Control -- Recurrent Neural Networks for AFR Estimation and Control in Spark Ignition Automotive Engines -- Intelligent Vehicle Power Management: An Overview -- An Integrated Diagnostic Process for Automotive Systems -- Automotive Manufacturing: Intelligent Resistance Welding -- Intelligent Control of Mobility Systems.
520 _aWhat is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the fields of neural networks (NN), fuzzy logic and evolutionary computation. This edited volume is the first of its kind, suitable to automotive researchers, engineers and students. It provides a representative sample of contemporary CI activities in the area of automotive technology. The volume consists of 13 chapters, including but not limited to these topics: vehicle diagnostics and vehicle system safety, control of vehicular systems, quality control of automotive processes, driver state estimation, safety of pedestrians, intelligent vehicles. All chapters contain overviews of state of the art, and several chapters illustrate their methodologies on examples of real-world systems. About the Editor: Danil Prokhorov began his technical career in St. Petersburg, Russia, after graduating with Honors from Saint Petersburg State University of Aerospace Instrumentation in 1992 (MS in Robotics). He worked as a research engineer in St. Petersburg Institute for Informatics and Automation, one of the institutes of the Russian Academy of Sciences. He came to the US in late 1993 for Ph.D. studies. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI. Upon his graduation from the EE Department of Texas Tech University, Lubbock, in 1997, he joined Ford to pursue application-driven research on neural networks and other machine learning algorithms. While at Ford, he took part in several production-bound projects including neural network based engine misfire detection. Since 2005 he is with Toyota Technical Center, Ann Arbor, MI, overseeing important mid- and long-term research projects in computational intelligence.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 0 _aAutomotive engineering.
650 1 4 _aEngineering.
650 2 4 _aAutomotive Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
700 1 _aProkhorov, Danil.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540792567
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v132
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-79257-4
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c500626
_d500626