000 | 03360nam a22006015i 4500 | ||
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001 | 978-981-16-5936-2 | ||
003 | DE-He213 | ||
005 | 20240423125410.0 | ||
007 | cr nn 008mamaa | ||
008 | 211002s2021 si | s |||| 0|eng d | ||
020 |
_a9789811659362 _9978-981-16-5936-2 |
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024 | 7 |
_a10.1007/978-981-16-5936-2 _2doi |
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050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
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_aCOM004000 _2bisacsh |
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_aUYQ _2thema |
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082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aSamanta, Debabrata. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aComputationally Intensive Statistics for Intelligent IoT _h[electronic resource] / _cby Debabrata Samanta, Amit Banerjee. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2021. |
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300 |
_aXX, 218 p. 53 illus., 11 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aStudies in Autonomic, Data-driven and Industrial Computing, _x2730-6445 |
|
505 | 0 | _aIntroduction to Intelligent IoT -- ML and Information Advancement platform in Intelligent IoT -- Machine Intelligence and Data Science for Intelligent IoT -- Approaches of Data Analytics in Intelligent Medicare utilizing IoT -- Trends and Applications of Intelligent IoT in Agriculture -- Transformation of Intelligent IoT in the Energy Sector -- Abnormality Diagnosis from Ambient Data: Intelligent IoT Data Sequences in Real Time -- Future of Intelligent IoT. | |
520 | _aThe book covers computational statistics, its methodologies and applications for IoT device. It includes the details in the areas of computational arithmetic and its influence on computational statistics, numerical algorithms in statistical application software, basics of computer systems, statistical techniques, linear algebra and its role in optimization techniques, evolution of optimization techniques, optimal utilization of computer resources, and statistical graphics role in data analysis. It also explores computational inferencing and computer model's role in design of experiments, Bayesian analysis, survival analysis and data mining in computational statistics. | ||
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aInternet of things. | |
650 | 0 | _aMedical informatics. | |
650 | 0 | _aQuantitative research. | |
650 | 0 |
_aMathematical statistics _xData processing. |
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650 | 1 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aInternet of Things. |
650 | 2 | 4 | _aHealth Informatics. |
650 | 2 | 4 | _aData Analysis and Big Data. |
650 | 2 | 4 | _aStatistics and Computing. |
700 | 1 |
_aBanerjee, Amit. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811659355 |
776 | 0 | 8 |
_iPrinted edition: _z9789811659379 |
776 | 0 | 8 |
_iPrinted edition: _z9789811659386 |
830 | 0 |
_aStudies in Autonomic, Data-driven and Industrial Computing, _x2730-6445 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-16-5936-2 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c177510 _d177510 |