Open AccessStudy on Association Rules Based on Multiple Types of Flexible Loads
Author(s) -
Feng Jiang,
Zhuang Cai,
Kai Zhang,
Keming Zhan,
Bohong Gu
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/827/1/012026
Subject(s) - association rule learning , association (psychology) , computer science , object (grammar) , data mining , space (punctuation) , connection (principal bundle) , database , artificial intelligence , engineering , structural engineering , epistemology , operating system , philosophy
At present, the comprehensive consideration of multiple types of flexible loads and the complementary characteristics in time and space are less considered, which results in the user’s response potential cannot be further explored. This paper takes flexible load as the research object, and proposes a method for the research of association rules based on multiple types of flexible loads. An association rule mining and evaluation model is established to form an intelligent offline database and a relative connection degree database. As a result, the correlation of various types of flexible loads is discovered through the cooperation of the two, so as to provide guidance for dispatching.