References
1. Caffoor I (2010) Perspective: a vision of a low-carbon water sector in 2050. Proc Inst Civil
Eng-Eng Sustain 163(1):9–14. https://doi.org/10.1680/ensu.2010.163.1.9
2. Boxall JB, Machell J, Dewis N, Gedman K and Saul A (2011) In: Dragan A. Savic and
John K. Banyard (eds) Operation, maintenance and performance in water distribution systems,
ICE, London. ISBN: 978-0-7277-4112-7.
3. SWIG (Sensors for Water Interest Group) (2007) ‘SCADA systems for future management
of assets’ 24 Jan 2007
4. Bingi P, Sharma MK, Godla JK (1999) Critical issues affecting an ERP implementation.
Inf Syst Manage 16(3):7
5. IBM (2014) Web ref. Retrieved from 30 Nov 2014
6. UKWIR (2019) Smart metering and smart networks for leakage management report. UK Water
Industry Research, London – ISBN: 978-1-84057-880-5
7. Conroy P, De Rosa S (2015) Framework for expenditure decision making: development
of service forecasting approaches. UK Water Industry Research Limited, London
8. Mounce SR, Douterelo I, Sharpe R, Boxall JB (2012) A bio-hydroinformatics application
of self-organizing map neural networks for assessing microbial and physico-chemical
water quality in distribution systems, Proceedings of 10th international conference on
hydroinformatics, Hamburg, Germany
9. Mounce SR, Jensen HJ, Boxall JB, Biggs CA (2012) Data mining T-RFLP profiles from water
system sampling using self-organising maps. Proceedings of 8th international conference on
natural computation and the 9th proceedings of international conference on fuzzy systems
and knowledge discovery (IEEE), vol 1, pp 219–223.
10. Mounce SR, Sharpe R, Speight V, Holden B, Boxall JB (2014) Knowledge discovery
from large disparate corporate databases using self-organising maps to help ensure supply of
high quality potable water. Proceedings of 11th international conference on hydroinformatics,
New York, USA
11. Ellis K, Mounce SR, Edwards J, Speight V, Jakomis N, Boxall JB (2015) Interpreting and
estimating the risk of iron failures, Computing and Control for the Water Industry (CCWI2015).
Procedia Eng 119:299–308
12. Blokker EJM, Furnass WR, Machell J, Mounce SR, Schaap PG, Boxall JB (2016) Relating
water quality and age in drinking water distribution systems using self-organising maps.
Environments 3(2):10. https://doi.org/10.3390/environments3020010
13. Mounce SR, Blokker EJM, Husband SP, Furnass WR, Schaap PG, Boxall JB (2016)
Multivariate data mining for estimating the rate of discoloration material accumulation in
drinking water distribution systems. IWA J Hydroinf 18(1):96–114
14. Mackey T, Mounce SR, Boxall JB, Cashman A (2017) A multivariate geospatial data-driven
approach to descriptive modelling of burst behaviour in a small island context. Proceedings
of computing and control for the water industry (CCWI2017), Sheffield, UK
15. Kohonen T (1990) The self-organizing map. Proc IEEE 78(9):1464–1480. http://www-01.ibm.
com/software/data/bigdata/what-is-big-data.html
16. Sharpe RL, Smith CJ, Biggs CA and Boxall JB, (2010) Pilot scale laboratory investigations
into the impact of steady state conditioning hydraulics on potable water discolouration.
Proceedings of 11th annual international symposium on water distribution systems analysis,
Arizona, USA, September
17. Ester M, Kriegel HP, Sander J, Xu X (1996) Simoudis E, Han J, Fayyad UM (eds)
A density-based algorithm for discovering clusters in large spatial databases with noise.
AAAI Press, Palo Alto, pp 226–231
18. Sammon JW (1969) A nonlinear mapping for data structure analysis. IEEE Trans Comput
C-18(5):401–409
24
S. R. Mounce
1. Caffoor I (2010) Perspective: a vision of a low-carbon water sector in 2050. Proc Inst Civil
Eng-Eng Sustain 163(1):9–14. https://doi.org/10.1680/ensu.2010.163.1.9
2. Boxall JB, Machell J, Dewis N, Gedman K and Saul A (2011) In: Dragan A. Savic and
John K. Banyard (eds) Operation, maintenance and performance in water distribution systems,
ICE, London. ISBN: 978-0-7277-4112-7.
3. SWIG (Sensors for Water Interest Group) (2007) ‘SCADA systems for future management
of assets’ 24 Jan 2007
4. Bingi P, Sharma MK, Godla JK (1999) Critical issues affecting an ERP implementation.
Inf Syst Manage 16(3):7
5. IBM (2014) Web ref. Retrieved from 30 Nov 2014
6. UKWIR (2019) Smart metering and smart networks for leakage management report. UK Water
Industry Research, London – ISBN: 978-1-84057-880-5
7. Conroy P, De Rosa S (2015) Framework for expenditure decision making: development
of service forecasting approaches. UK Water Industry Research Limited, London
8. Mounce SR, Douterelo I, Sharpe R, Boxall JB (2012) A bio-hydroinformatics application
of self-organizing map neural networks for assessing microbial and physico-chemical
water quality in distribution systems, Proceedings of 10th international conference on
hydroinformatics, Hamburg, Germany
9. Mounce SR, Jensen HJ, Boxall JB, Biggs CA (2012) Data mining T-RFLP profiles from water
system sampling using self-organising maps. Proceedings of 8th international conference on
natural computation and the 9th proceedings of international conference on fuzzy systems
and knowledge discovery (IEEE), vol 1, pp 219–223.
10. Mounce SR, Sharpe R, Speight V, Holden B, Boxall JB (2014) Knowledge discovery
from large disparate corporate databases using self-organising maps to help ensure supply of
high quality potable water. Proceedings of 11th international conference on hydroinformatics,
New York, USA
11. Ellis K, Mounce SR, Edwards J, Speight V, Jakomis N, Boxall JB (2015) Interpreting and
estimating the risk of iron failures, Computing and Control for the Water Industry (CCWI2015).
Procedia Eng 119:299–308
12. Blokker EJM, Furnass WR, Machell J, Mounce SR, Schaap PG, Boxall JB (2016) Relating
water quality and age in drinking water distribution systems using self-organising maps.
Environments 3(2):10. https://doi.org/10.3390/environments3020010
13. Mounce SR, Blokker EJM, Husband SP, Furnass WR, Schaap PG, Boxall JB (2016)
Multivariate data mining for estimating the rate of discoloration material accumulation in
drinking water distribution systems. IWA J Hydroinf 18(1):96–114
14. Mackey T, Mounce SR, Boxall JB, Cashman A (2017) A multivariate geospatial data-driven
approach to descriptive modelling of burst behaviour in a small island context. Proceedings
of computing and control for the water industry (CCWI2017), Sheffield, UK
15. Kohonen T (1990) The self-organizing map. Proc IEEE 78(9):1464–1480. http://www-01.ibm.
com/software/data/bigdata/what-is-big-data.html
16. Sharpe RL, Smith CJ, Biggs CA and Boxall JB, (2010) Pilot scale laboratory investigations
into the impact of steady state conditioning hydraulics on potable water discolouration.
Proceedings of 11th annual international symposium on water distribution systems analysis,
Arizona, USA, September
17. Ester M, Kriegel HP, Sander J, Xu X (1996) Simoudis E, Han J, Fayyad UM (eds)
A density-based algorithm for discovering clusters in large spatial databases with noise.
AAAI Press, Palo Alto, pp 226–231
18. Sammon JW (1969) A nonlinear mapping for data structure analysis. IEEE Trans Comput
C-18(5):401–409
24
S. R. Mounce