A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Fundamentals of speech recognition
Fundamentals of speech recognition
Induction of fuzzy decision trees
Fuzzy Sets and Systems
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
HydroSense: infrastructure-mediated single-point sensing of whole-home water activity
Proceedings of the 11th international conference on Ubiquitous computing
Designing environmental software applications based upon an open sensor service architecture
Environmental Modelling & Software
Bias of importance measures for multi-valued attributes and solutions
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Data-driven modeling approaches to support wastewater treatment plant operation
Environmental Modelling & Software
IEEE Transactions on Information Theory
Environmental Modelling & Software
An autonomous and intelligent expert system for residential water end-use classification
Expert Systems with Applications: An International Journal
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The rapid dissemination of residential water end-use (e.g. shower, clothes washer, etc.) consumption data to the customer via a web-enabled portal interface is becoming feasible through the advent of high resolution smart metering technologies. However, in order to achieve this paradigm shift in residential customer water use feedback, an automated approach for disaggregating complex water flow trace signatures into a registry of end-use event categories needs to be developed. This outcome is achieved by applying a hybrid combination of gradient vector filtering, Hidden Markov Model (HMM) and Dynamic Time Warping Algorithm (DTW) techniques on an existing residential water end-use database of 252 households located in South-east Queensland, Australia having high resolution water meters (0.0139 L/pulse), remote data transfer loggers (5 s logging) and completed household water appliance audits. The approach enables both single independent events (e.g. shower event) and combined events (i.e. several overlapping single events) to be disaggregated from flow data into a comprehensive end-use event registry. Complex blind source separation of concurrently occurring water end use events (e.g. shower and toilet flush occurring in same time period) is the primary focus of this present study. Validation of the developed model is achieved through an examination of 50 independent combined events.