Title :
The novel rule induction approach to dynamic big data in green energy
Author :
Chun-Che Huang ; Tseng, Tzu-Liang Bill ; Ming-Xuan Zhou
Author_Institution :
Dept. of Manage. Inf., Nat. Chi Nan Univ., Taiwan
Abstract :
With concerns about climate change growing it could be that green energy will begin to play a major role. Green Energy requires to resolve the optimization problem of electronic distribution, control, and storage with decision rule support. Due to the characteristics of green energy data nature - time dependency and variance, and big data, a novel approach to induct rules is required without re-computing rule sets from the very beginning, when new objects are updated to information system. The proposed approach updates rule sets by partly modifying original rule sets, hence a lot of time are saved, and it is especially useful when extracting rules from big data sets. The rules comparison helps decision maker to explore the marketing and qualified decision for renew energy distribution.
Keywords :
Big Data; climatology; data mining; decision making; green computing; optimisation; climate change; decision maker; decision rule support; dynamic big data; electronic distribution; energy distribution; green energy data nature; information system; optimization problem; rule induction approach; time dependency; time variance; Big data; Data mining; Distributed databases; Green products; Heuristic algorithms; Renewable energy sources; big data; data mining; decision rules; green/renew energy; rule induction;
Conference_Titel :
Science and Information Conference (SAI), 2015
Conference_Location :
London
DOI :
10.1109/SAI.2015.7237334