An autonomous and intelligent expert system for residential water end-use classification
作者：
Highlights：
• Smart metering technology enables the capture of high resolution water consumption data.
• Intelligent algorithms developed to autonomously categorise single and combined water end use events.
• Hybrid combination of HMM, DTW and probability techniques applied to pattern recognition problem.
• Adaptive functionality embedded to enable model to self-train when applied in new cities or regions.
• User friendly expert system developed to autonomously disaggregate water consumption data into end use categories.
摘要
•Smart metering technology enables the capture of high resolution water consumption data.•Intelligent algorithms developed to autonomously categorise single and combined water end use events.•Hybrid combination of HMM, DTW and probability techniques applied to pattern recognition problem.•Adaptive functionality embedded to enable model to self-train when applied in new cities or regions.•User friendly expert system developed to autonomously disaggregate water consumption data into end use categories.
论文关键词：Water end-use event,Water micro-component,Residential water flow trace disaggregation,Hidden Markov Model,Dynamic time warping algorithm,Gradient Vector Filtering,Adaptive analysis,Adaptive function,Water demand management
论文评审过程：Available online 31 July 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.049
