Hidden Markov Models Based Appliance
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-15-1860-7_7
Reference29 articles.
1. Aiad M, Lee PH (2018a) Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach. Sustain Cities Soc 43:487–494. https://doi.org/10.1016/j.scs.2018.08.020
2. Aiad M, Lee PH (2018b) Modelling and power estimation of continuously varying residential loads using a quantized continuous-state hidden markov model. In: Proceedings of the 2nd international conference on machine learning and soft computing. ACM, pp 180–184
3. Bengio Y, Frasconi P (1995) An input output HMM architecture. In: Advances in neural information processing systems, pp 427–434
4. Chen S, Gao F, Liu T (2017) Load identification based on factorial hidden Markov model and online performance analysis. In: 2017 13th IEEE conference on automation science and engineering (CASE). IEEE, pp 1249–1253
5. Choi K-S, Yang B-W (2016) NILM method using FHMM reflecting correlation between two appliances. Int Inf Inst (Tokyo) Inf 19(2):555
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