Improving Knowledge-Based Systems with statistical techniques, text mining, and neural networks for non-technical loss detection

作者：

Highlights：

• Several knowledge acquisition processes were made with Endesa staff.

• The knowledge of inspectors was successfully translated to rules.

• A knowledge-based expert system for non-technical losses detection was created.

• The system was improved with text mining, neural networks and statistical techniques.

• The proposed system is applied in Endesa databases.

摘要

•Several knowledge acquisition processes were made with Endesa staff.•The knowledge of inspectors was successfully translated to rules.•A knowledge-based expert system for non-technical losses detection was created.•The system was improved with text mining, neural networks and statistical techniques.•The proposed system is applied in Endesa databases.

论文关键词：Expert system,Power distribution,Non-technical losses,Neural network,Text mining

论文评审过程：Received 22 December 2013, Revised 12 August 2014, Accepted 13 August 2014, Available online 23 August 2014.

论文官网地址：https://doi.org/10.1016/j.knosys.2014.08.014