scholarly journals Enhancing Residential Water End Use Pattern Recognition Accuracy Using Self-Organizing Maps and K-Means Clustering Techniques: Autoflow v3.1

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1221 ◽  
Author(s):  
Ao Yang ◽  
Hong Zhang ◽  
Rodney Stewart ◽  
Khoi Nguyen
Keyword(s):  
Pattern Recognition ◽  
Water Consumption ◽  
Recognition Accuracy ◽  
Clustering Algorithms ◽  
Self Organizing Maps ◽  
Residential Water Consumption ◽  
End Use ◽  
Use Studies ◽  
Residential Water ◽  
Self Organizing

The aim of residential water end-use studies is to disaggregate water consumption into different water end-use categories (i.e., shower, toilet, etc.). The authors previously developed a beta application software (i.e., Autoflow v2.1) that provides an intelligent platform to autonomously categorize residential water consumption data and generate management analysis reports. However, the Autoflow v2.1 software water end use event recognition accuracy achieved was between 75 to 90%, which leaves room for improvement. In the present study, a new module augmented to the existing procedure improved flow disaggregation accuracy, which resulted in Autoflow v3.1. The new module applied self-organizing maps (SOM) and K-means clustering algorithms for undertaking an initial pre-grouping of water end-use events before the existing pattern recognition procedures were applied (i.e., ANN, HMM, etc.) For validation, a dataset consisting of over 100,000 events from 252 homes in Australia were employed to verify accuracy improvements derived from augmenting the new hybrid SOM and K-means algorithm techniques into the existing Autoflow v2.1 software. The water end use event categorization accuracy ranged from 86 to 94.2% for the enhanced model (Autoflow v3.1), which was a 1.7 to 9% improvement on event categorization.

scholarly journals What does rebounding water use look like? An examination of post-drought and post-flood water end-use demand in Queensland, Australia

2014 ◽  
Vol 14 (4) ◽  
pp. 561-568 ◽  
Author(s):  
C. D. Beal ◽  
A. Makki ◽  
R. A. Stewart
Keyword(s):  
Water Use ◽  
Water Consumption ◽  
Demand Management ◽  
Management Policy ◽  
Dry Period ◽  
Residential Water Consumption ◽  
End Use ◽  
Capacity Data ◽  
Residential Water

Rebounding water use behaviour has been observed in communities that have experienced plentiful water supply following a very dry period. However, the drivers of such rebounds in water consumption are varied and not well understood. Knowledge of such drivers can greatly assist managers towards proactive demand management, modelling and timely promotion of water efficient behaviours. Total and end-use residential water consumption has been tracked in South East Queensland, Australia for a sample of up to 252 homes in post-drought conditions (dam supplies growing but water restrictions continued, changed water use behaviours still ‘fresh’), and during and post-flooding conditions (eased restrictions, 100% dam capacity). Data on end-use water consumption trends using nearly 3 years of residential water end-use data have revealed several interesting patterns of consumption such as a delayed return to pre-drought use, the influence of climate and end-use specific rebounds (e.g. indoor versus outdoor use). The end-use data have helped to identify the drivers of rebounding water consumption which appear to include environmental cues (rainfall, temperature), social cues (e.g. government encouraging consumers to turn on tap) and a gradual general reduction in conservative water use behaviours. The paper concludes with a discussion of how this knowledge can be used to inform long-term demand management policy, particularly in variable climates.

Self Organizing Maps, Pattern Recognition and Financial Crises

2011 ◽  
Author(s):  
Sylvain Barthelemy ◽  
Pascal Devaux ◽  
Francois Faure ◽  
Matthieu Pautonnier
Keyword(s):  
Pattern Recognition ◽  
Financial Crises ◽  
Self Organizing Maps ◽  
Self Organizing

scholarly journals The Effect of Social Behavior on Residential Water Consumption

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1184
Author(s):  
Daniel Morales Martínez ◽  
Alexandre Gori Maia
Keyword(s):  
Water Consumption ◽  
Spatial Dependence ◽  
Regression Models ◽  
Innovative Strategy ◽  
Peer Effect ◽  
Household Level ◽  
Level Data ◽  
Household Water ◽  
Residential Water Consumption ◽  
Residential Water

We analyze how residential water consumption is influenced by the consumption of households belonging to the same social group (peer effect). Analyses are based on household-level data provided by the Brazilian Household Budget Survey and use an innovative strategy that estimates the spatial dependence of water consumption while simultaneously controlling for potential sources of sample selectivity and endogeneity. The estimates of our quantile regression models highlight that, conditional on household characteristics, the greater the household water consumption, the greater the peer effect. In other words, the overconsumption of residential water seems to be influenced mainly by the behavior of social peers.

scholarly journals Forecasting Residential Water Consumption in California: Rethinking Model Selection

2020 ◽  
Vol 56 (1) ◽  
Author(s):  
Steven Buck ◽  
Maximilian Auffhammer ◽  
Hilary Soldati ◽  
David Sunding
Keyword(s):  
Model Selection ◽  
Water Consumption ◽  
Residential Water Consumption ◽  
Residential Water

Developing a demand model integrating end uses of water (DMEUW): structure and process of integration

2015 ◽  
Vol 71 (4) ◽  
pp. 529-537 ◽  
Author(s):  
R. C. Sarker ◽  
S. Gato-Trinidad
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Water Demand ◽  
Daily Rainfall ◽  
Demand Model ◽  
Data Set ◽  
Residential Water Consumption ◽  
End Use ◽  
Hypertext Markup Language ◽  
End Uses

The process of developing an integrated water demand model integrating end uses of water has been presented. The model estimates and forecasts average daily water demand based on the end-use pattern and trend of residential water consumption, daily rainfall and temperature, water restrictions and water conservation programmes. The end-use model uses the latest end-use data set collected from Yarra Valley Water, Australia. A computer interface has also been developed using hypertext markup language and hypertext pre-processor. The developed model can be used by water authorities and water resource planners in forecasting water demand and by household owners in determining household water consumption.

Self-Organizing Map Application for Iris Recognition

2014 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Anna Sedrak Hovakimyan ◽  
Siranush Gegham Sargsyan ◽  
Arshak Nazaryan
Keyword(s):  
Pattern Recognition ◽  
Problem Solving ◽  
Iris Recognition ◽  
Classification Problem ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
The Neural Network ◽  
Human Iris ◽  
Iris Patterns ◽  
Self Organizing

Human iris is  a good subject of biometrical identification, since  iris patterns are unique like fingerprints. Iris is well protected against damage, unlike fingerprints, which can be harder to recognize after years of certain types of manual labor.A problem of iris recognition is considered in the paper. In machine learning, pattern recognition is the assignment of a label to a given input value. Pattern classification is an example of pattern recognition: it attempts to assign each input value to one of a given set of classes. Nowadays various techniques are used for this purpose, and in particular artificial neural networks.For iris recognition problem solving  Kohenen Self Organizing Maps are suggested to use. The software for iris recognition is developed  which is customizable and allows to select the appropriate parameters of the neural network to obtain the most satisfactory results. The developed Self-Organizing Map Library of classes can be used for various kinds of object classification problem solving as well as for any problems suitable to solve with Self-Organizing Maps.

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