Markov model (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Markov model" in English language version.

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9doi.org

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2acm.org

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acm.org

dl.acm.org

Theocharous, G. (2002). Hierarchical Learning and Planning in Partially Observable Markov Decision Processes (PhD). Michigan State University.
Luhr, S.; Bui, H. H.; Venkatesh, S.; West, G. A. W. (2003). "Recognition of Human Activity through Hierarchical Stochastic Learning". PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications. pp. 416–422. CiteSeerX 10.1.1.323.928. doi:10.1109/PERCOM.2003.1192766. ISBN 978-0-7695-1893-0. S2CID 13938580.

doi.org

Kaelbling, L. P.; Littman, M. L.; Cassandra, A. R. (1998). "Planning and acting in partially observable stochastic domains". Artificial Intelligence. 101 (1–2): 99–134. CiteSeerX 10.1.1.390.8474. doi:10.1016/S0004-3702(98)00023-X. ISSN 0004-3702.
Fine, S.; Singer, Y. (1998). "The hierarchical hidden markov model: Analysis and applications". Machine Learning. 32 (1): 41–62. doi:10.1023/A:1007469218079.
Bui, H. H.; Venkatesh, S.; West, G. (2002). "Policy recognition in the abstract hidden markov model". Journal of Artificial Intelligence Research. 17: 451–499. doi:10.1613/jair.839. hdl:10536/DRO/DU:30044252.
Luhr, S.; Bui, H. H.; Venkatesh, S.; West, G. A. W. (2003). "Recognition of Human Activity through Hierarchical Stochastic Learning". PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications. pp. 416–422. CiteSeerX 10.1.1.323.928. doi:10.1109/PERCOM.2003.1192766. ISBN 978-0-7695-1893-0. S2CID 13938580.
Pratas, D.; Hosseini, M.; Pinho, A. J. (2017). "Substitutional tolerant Markov models for relative compression of DNA sequences". PACBB 2017 – 11th International Conference on Practical Applications of Computational Biology & Bioinformatics, Porto, Portugal. pp. 265–272. doi:10.1007/978-3-319-60816-7_32. ISBN 978-3-319-60815-0.
Pratas, D.; Pinho, A. J.; Ferreira, P. J. S. G. (2016). "Efficient compression of genomic sequences". Data Compression Conference (DCC), 2016. IEEE. pp. 231–240. doi:10.1109/DCC.2016.60. ISBN 978-1-5090-1853-6. S2CID 14230416.
de Souza e Silva, E.G.; Legey, L.F.L.; de Souza e Silva, E.A. (2010). "Forecasting oil price trends using wavelets and hidden Markov models". Energy Economics. 32 (6): 1507. Bibcode:2010EneEc..32.1507D. doi:10.1016/j.eneco.2010.08.006.
Carpinone, A; Giorgio, M; Langella, R.; Testa, A. (2015). "Markov chain modeling for very-short-term wind power forecasting". Electric Power Systems Research. 122: 152–158. Bibcode:2015EPSR..122..152C. doi:10.1016/j.epsr.2014.12.025.
Munkhammar, J.; van der Meer, D.W.; Widén, J. (2019). "Probabilistic forecasting of high-resolution clear-sky index time-series using a Markov-chain mixture distribution model". Solar Energy. 184: 688–695. Bibcode:2019SoEn..184..688M. doi:10.1016/j.solener.2019.04.014. S2CID 146076100.

handle.net

hdl.handle.net

Bui, H. H.; Venkatesh, S.; West, G. (2002). "Policy recognition in the abstract hidden markov model". Journal of Artificial Intelligence Research. 17: 451–499. doi:10.1613/jair.839. hdl:10536/DRO/DU:30044252.

harvard.edu

ui.adsabs.harvard.edu

de Souza e Silva, E.G.; Legey, L.F.L.; de Souza e Silva, E.A. (2010). "Forecasting oil price trends using wavelets and hidden Markov models". Energy Economics. 32 (6): 1507. Bibcode:2010EneEc..32.1507D. doi:10.1016/j.eneco.2010.08.006.
Carpinone, A; Giorgio, M; Langella, R.; Testa, A. (2015). "Markov chain modeling for very-short-term wind power forecasting". Electric Power Systems Research. 122: 152–158. Bibcode:2015EPSR..122..152C. doi:10.1016/j.epsr.2014.12.025.
Munkhammar, J.; van der Meer, D.W.; Widén, J. (2019). "Probabilistic forecasting of high-resolution clear-sky index time-series using a Markov-chain mixture distribution model". Solar Energy. 184: 688–695. Bibcode:2019SoEn..184..688M. doi:10.1016/j.solener.2019.04.014. S2CID 146076100.

jair.org

Bui, H. H.; Venkatesh, S.; West, G. (2002). "Policy recognition in the abstract hidden markov model". Journal of Artificial Intelligence Research. 17: 451–499. doi:10.1613/jair.839. hdl:10536/DRO/DU:30044252.

psu.edu

citeseerx.ist.psu.edu

Kaelbling, L. P.; Littman, M. L.; Cassandra, A. R. (1998). "Planning and acting in partially observable stochastic domains". Artificial Intelligence. 101 (1–2): 99–134. CiteSeerX 10.1.1.390.8474. doi:10.1016/S0004-3702(98)00023-X. ISSN 0004-3702.
Luhr, S.; Bui, H. H.; Venkatesh, S.; West, G. A. W. (2003). "Recognition of Human Activity through Hierarchical Stochastic Learning". PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications. pp. 416–422. CiteSeerX 10.1.1.323.928. doi:10.1109/PERCOM.2003.1192766. ISBN 978-0-7695-1893-0. S2CID 13938580.

sciencedirect.com

de Souza e Silva, E.G.; Legey, L.F.L.; de Souza e Silva, E.A. (2010). "Forecasting oil price trends using wavelets and hidden Markov models". Energy Economics. 32 (6): 1507. Bibcode:2010EneEc..32.1507D. doi:10.1016/j.eneco.2010.08.006.

semanticscholar.org

api.semanticscholar.org

Luhr, S.; Bui, H. H.; Venkatesh, S.; West, G. A. W. (2003). "Recognition of Human Activity through Hierarchical Stochastic Learning". PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications. pp. 416–422. CiteSeerX 10.1.1.323.928. doi:10.1109/PERCOM.2003.1192766. ISBN 978-0-7695-1893-0. S2CID 13938580.
Pratas, D.; Pinho, A. J.; Ferreira, P. J. S. G. (2016). "Efficient compression of genomic sequences". Data Compression Conference (DCC), 2016. IEEE. pp. 231–240. doi:10.1109/DCC.2016.60. ISBN 978-1-5090-1853-6. S2CID 14230416.
Munkhammar, J.; van der Meer, D.W.; Widén, J. (2019). "Probabilistic forecasting of high-resolution clear-sky index time-series using a Markov-chain mixture distribution model". Solar Energy. 184: 688–695. Bibcode:2019SoEn..184..688M. doi:10.1016/j.solener.2019.04.014. S2CID 146076100.

worldcat.org

search.worldcat.org

Kaelbling, L. P.; Littman, M. L.; Cassandra, A. R. (1998). "Planning and acting in partially observable stochastic domains". Artificial Intelligence. 101 (1–2): 99–134. CiteSeerX 10.1.1.390.8474. doi:10.1016/S0004-3702(98)00023-X. ISSN 0004-3702.