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 doi:

DOI: 10.3724/SP.J.1219.2013.00765

Information and Control (信息与控制) 2013/42:6 PP.765-771

## Multiple Outlier Detection Method for Linear Regression Model and Its Energy Conservation Application

• LIU Dandan 1,2   CHEN Qijun 1   MORI Kazuyuki 3
• 1.School of Electronics and Information, Tongji University, Shanghai 201804, China;
• 2.School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
• 3.Advanced Technology R&D Center, Mitsubishi Electric Corperation, Amagasaki 661-8661, Japan

Abstract：
The energy consumption of the office equipment can be described by linear regression model. For the model, a multiple outlier detection algorithm based on single-link hierarchical clustering and LTS (least trimmed squares) estimator is proposed. This method is validated in different types of typical data sets. And the results prove that it has excellent performance. Then it is applied to office equipment energy consumption data sets. The experiments show that it has better ability to deal with the masking and swamping problems than other algorithms. Also, the method can not only correctly identify the outliers but also provide abnormal degree of outliers. The managers can develop the reasonable energy management solutions and achieve the purpose of energy saving.

Key words：single linkage hierarchical clustering algorithm,linear regression model,outlier detection,least trimmed squares estimator,masking problem,swamping problem

ReleaseDate：2015-04-15 18:52:46

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