| 000 | 04758naaaa2201153uu 4500 | ||
|---|---|---|---|
| 003 | BUT | ||
| 005 | 20230404144411.0 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20220111s2021 xx |||||o ||| eng|| d | ||
| 020 | _a9783036511610 | ||
| 020 | _a9783036511603 | ||
| 040 |
_aoapen _coapen |
||
| 041 | 0 | _aeng | |
| 080 | _a004.8 | ||
| 100 | 1 |
_aLytras, Miltiadis _4edt |
|
| 245 | 1 | 0 |
_aArtificial Intelligence and Cognitive Computing _bMethods, Technologies, Systems, Applications and Policy Making |
| 260 |
_aBasel, Switzerland _bMDPI - Multidisciplinary Digital Publishing Institute _c2021 |
||
| 300 | _a1 electronic resource (278 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aArtificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by/4.0/ _2cc |
||
| 546 | _aEnglish | ||
| 650 | 0 |
_aИскусственный интеллект _94518 |
|
| 653 | _adata mining | ||
| 653 | _adecision-making system | ||
| 653 | _arough set | ||
| 653 | _amixed integer linear programming | ||
| 653 | _aassembly clearance | ||
| 653 | _adiesel engine quality | ||
| 653 | _aInternet of things | ||
| 653 | _aWireless nodes | ||
| 653 | _aHybrid clustering | ||
| 653 | _aMulti-hop routing | ||
| 653 | _aNetwork lifetime | ||
| 653 | _aArtificial intelligence | ||
| 653 | _adata envelopment analysis | ||
| 653 | _adecision making | ||
| 653 | _aartificial intelligence | ||
| 653 | _aperformance | ||
| 653 | _avisual analytics | ||
| 653 | _asystem | ||
| 653 | _aair quality | ||
| 653 | _aspatiotemporal | ||
| 653 | _amultivariate | ||
| 653 | _adimension reduction | ||
| 653 | _aclustering | ||
| 653 | _aregular patterns | ||
| 653 | _aanomalies | ||
| 653 | _aspeech recognition | ||
| 653 | _aLong Short Term Memory (LSTM) | ||
| 653 | _aspeech output correction | ||
| 653 | _amost-matching | ||
| 653 | _aempirical correlations | ||
| 653 | _arheological properties | ||
| 653 | _areal-time | ||
| 653 | _awater-based drill-in fluid | ||
| 653 | _aartificial neural network | ||
| 653 | _aelastic parameters | ||
| 653 | _aPoisson’s ratio | ||
| 653 | _asandstone | ||
| 653 | _aself-adaptive differential evolution | ||
| 653 | _atotal organic carbon | ||
| 653 | _abarnett shale | ||
| 653 | _adevonian shale | ||
| 653 | _afishbone multilateral wells | ||
| 653 | _apredictive models | ||
| 653 | _awell productivity | ||
| 653 | _ainternational research | ||
| 653 | _aknowledge map visualization | ||
| 653 | _apolicy documents quantification | ||
| 653 | _aresearch hotspot | ||
| 653 | _apolicy keyword | ||
| 653 | _aminimum miscibility pressure (MMP) | ||
| 653 | _aCO2 flooding | ||
| 653 | _anew models | ||
| 653 | _aface recognition | ||
| 653 | _asecurity | ||
| 653 | _aspoofing | ||
| 653 | _ahistogram of oriented gradients | ||
| 653 | _asmart cities | ||
| 653 | _adeep learning | ||
| 653 | _aLSTM | ||
| 653 | _aneural networks | ||
| 653 | _alocation prediction | ||
| 653 | _atrajectories | ||
| 653 | _asmart tourism | ||
| 653 | _astatic Young’s modulus | ||
| 653 | _asandstone formations | ||
| 653 | _amachine learning | ||
| 653 | _an/a | ||
| 700 | 1 |
_aVisvizi, Anna _4edt |
|
| 700 | 1 |
_aLytras, Miltiadis _4oth |
|
| 700 | 1 |
_aVisvizi, Anna _4oth |
|
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/3715 _70 _zDownload |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/76299 _70 _zDescription |
| 909 |
_c4 _dDarya Shvetsova |
||
| 942 |
_2udc _cEE |
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| 999 |
_c6316 _d6316 |
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