Title :
A Brief Introduction to Classification for Smart Grid
Author :
Chun-Wei Tsai ; Pelov, Alexander ; Ming-Chao Chiang ; Chu-Sing Yang ; Tzung-Pei Hong
Author_Institution :
Dept. of Appl. Inf. & Multimedia, Chia Nan Univ. of Pharmacy & Sci., Tainan, Taiwan
Abstract :
There is no doubt about the potentials of smart grid, for the traditional power grid has been kind of out of date, in terms of not only its infrastructure but also its restrictions on the way information is communicated. To provide better and smarter services via smart grid, the first thing we have to do is to make it more intelligent. Among the technologies that can be applied to smart grid to make it more intelligent, data mining will certainly play a vital role. This paper begins with a brief introduction to smart grid, followed by a discussion on the supervised learning (classification) and the unsupervised learning (clustering). Several open and possible research issues are then given to depict the future trends of smart grid.
Keywords :
data mining; learning (artificial intelligence); power engineering computing; smart power grids; data mining; smart grid classification; supervised learning; unsupervised learning; Algorithm design and analysis; Clustering algorithms; Data mining; Market research; Smart grids; Smart grid; and machine learning; data mining;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
DOI :
10.1109/SMC.2013.495