Author:
Lekshmi R. Chandran,Ilango K.,Manjula G. Nair,Ashish V.,Aleena John,Abhijith G.,Anagha H. Kumar,Akhil Raghavendra
Reference23 articles.
1. Hart, G.W.: Nonintrusive appliance load monitoring. Proc. IEEE 80(12), 1870–1891 (1992)
2. Hui, .L.Y., Logenthiran, T., Woo, W.L.: Non-intrusive appliance load monitoring and identification for smart home. In: 2016 IEEE 6th International Conference on Power Systems (ICPS), pp. 1–6. New Delhi (2016)
3. Sreevidhya, C., Kumar, M., Karuppasamy, I.: Design and implementation of non-intrusive load monitoring using machine learning algorithm for appliance monitoring. In: 2019 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), pp. 1–6. Tamil Nadu, India (2019). https://doi.org/10.1109/INCOS45849.2019.8951312
4. Yang, H., Chang, H., Lin, C.: Design a neural network for features selection in non-intrusive monitoring of industrial electrical loads. In: 2007 11th International Conference on Computer Supported Cooperative Work in Design, pp. 1022–1027. Melbourne, VIC (2007)
5. Hasan, T., Javed, F., Arshad, N.: An empirical investigation of V-I trajectory based load signatures for non-intrusive load monitoring. In: 2014 IEEE PES General Meeting | Conference and Exposition, p. 1. National Harbor, MD (2014)
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