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Machine Learning Approaches to Non-Intrusive Load Monitoring pp 31–90Cite as

HMM Based Approach

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Abstract

Approaches based on hidden Markov models (HMMs) have been devoted particular attention in the last years. AFAMAP (Additive Factorial Approximate Maximum a Posteriori) has been introduced in Kolter and Jaakkola to reduce the computational burden of FHMM. The algorithm bases its operation on additive and difference FHMM, and it constrains the posterior probability to require only one HMM change state at any given time.

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Notes

  1. 1.

    http://www-01.ibm.com/software/commerce/optimization/cplex-optimizer/.

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  1. Marche Polytechnic University, Via Brecce Bianche 12, Italy

    Roberto Bonfigli & Stefano Squartini

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  1. Roberto Bonfigli
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  2. Stefano Squartini
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Bonfigli, R., Squartini, S. (2020). HMM Based Approach. In: Machine Learning Approaches to Non-Intrusive Load Monitoring. SpringerBriefs in Energy. Springer, Cham. https://doi.org/10.1007/978-3-030-30782-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-30782-0_4

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  • Online ISBN: 978-3-030-30782-0

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