Rough Set Based Rule Induction with Elimination of Outdated Big Data in Renewable Energy Equipment Promotion

碩士 === 國立暨南國際大學 === 資訊管理學系 === 103 === Energy problem has become a major challenge in twenty-first century, countries around the world are looking for solutions. Development of renewable energy is one of the important means to solve the energy crisis. Renewable energy data has the characteristics of...

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Bibliographic Details
Main Authors: Pei-An Wang, 王培安
Other Authors: Chun-Che Huang
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/06891860374051605162
Description
Summary:碩士 === 國立暨南國際大學 === 資訊管理學系 === 103 === Energy problem has become a major challenge in twenty-first century, countries around the world are looking for solutions. Development of renewable energy is one of the important means to solve the energy crisis. Renewable energy data has the characteristics of multi-attribute and across different areas, many studies use data mining from renewable energy data to get viable rule induction, thereby achieve a long-term energy planning. For multi-attribute problems and rule induction solution, rough set is a very suitable method. In addition, appears of big data change the previous data mining mode. Because of the characteristics of big data, when data reuse should be avoided constantly recalculate. For handle the changing big data, dynamic database calculus became an integral part. However, past studies for big data dynamic database tend to focus on incremental manner, but has neglected decrement situation. Therefore, this study will be from the perspective of big data to explore rough set rule induction whit decrement operation assessment program used in the promotion of renewable energy sources and presents case evidence.