| 000 | 02916naaaa2200625uu 4500 | ||
|---|---|---|---|
| 003 | BUT | ||
| 005 | 20230412140029.0 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20210210s2021 gerx |||||o ||||eng|| d | ||
| 020 | _a9783662627464 | ||
| 040 |
_aoapen _coapen |
||
| 041 | 0 | _aeng | |
| 042 | _adc | ||
| 080 | _a004.85 | ||
| 100 | 1 |
_aBeyerer, Jürgen _4edt |
|
| 245 | 1 | 0 |
_aMachine Learning for Cyber Physical Systems _bSelected papers from the International Conference ML4CPS 2020 |
| 260 |
_bSpringer Nature _c2021 |
||
| 300 | _a1 electronic resource (130 p.) | ||
| 490 | 1 | _aTechnologien für die intelligente Automation | |
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aThis open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. | ||
| 540 |
_aCreative Commons _fby/4.0/ _2cc |
||
| 546 | _aEnglish | ||
| 650 | 7 |
_aCommunications engineering / telecommunications _2bicssc |
|
| 650 | 7 |
_aComputer networking & communications _2bicssc |
|
| 653 | _aCyber-physical systems, IoT | ||
| 653 | _aCommunications Engineering, Networks | ||
| 653 | _aComputer Systems Organization and Communication Networks | ||
| 653 | _aCyber-Physical Systems | ||
| 653 | _aComputer Engineering and Networks | ||
| 653 | _aMachine Learning | ||
| 653 | _aArtificial Intelligence | ||
| 653 | _aCognitive Robotics | ||
| 653 | _aInternet of Things | ||
| 653 | _aComputational intelligence | ||
| 653 | _aComputer-based algorithms | ||
| 653 | _aSmart grid | ||
| 653 | _aOpen Access | ||
| 653 | _aIndustry 4.0 | ||
| 653 | _aElectrical engineering | ||
| 653 | _aCybernetics & systems theory | ||
| 653 | _aCommunications engineering / telecommunications | ||
| 653 | _aComputer networking & communications | ||
| 700 | 1 |
_aMaier, Alexander _4edt |
|
| 700 | 1 |
_aNiggemann, Oliver _4edt |
|
| 700 | 1 |
_aBeyerer, Jürgen _4oth |
|
| 700 | 1 |
_aMaier, Alexander _4oth |
|
| 700 | 1 |
_aNiggemann, Oliver _4oth |
|
| 830 |
_94557 _aTechnologien für die intelligente Automation |
||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://library.oapen.org/bitstream/20.500.12657/46102/1/2021_Book_MachineLearningForCyberPhysica.pdf _70 _zDownload |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/33766 _70 _zDescription |
| 909 |
_c197 _dKhurliman Arzieva |
||
| 942 |
_2udc _cEE |
||
| 999 |
_c6419 _d6419 |
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