# HMM Based Approach

Chapter

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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.

## Keywords

Hidden Markov Model Working state Power consumption Active power Factorial Hidden Markov Model Rest-of-the-world model Constrained optimization Reactive power Finite State Machine Footprint## References

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