[Aksela, K., Aksela,M. and Vahala, R. (2009). Leakage detection in a real distribution network using a SOM, Urban Water Journal 6(4): 279-289.10.1080/15730620802673079]Search in Google Scholar
[Alcala, C.F. and Qin, S.J. (2009). Reconstruction-based contribution for process monitoring, Automatica 45(7): 1593-1600.10.1016/j.automatica.2009.02.027]Search in Google Scholar
[Beghi, A., Brignoli, R., Cecchinato, L., Menegazzo, G., Rampazzo, M. and Simmini, F. (2016). Data-driven fault detection and diagnosis for HVAC water chillers, Control Engineering Practice 53: 79-91.10.1016/j.conengprac.2016.04.018]Search in Google Scholar
[Chiang, L.H., Rusell, E. and Braatz, R.D. (2001). Fault Detection and Diagnosis in Industrial Systems, Springer, London.10.1007/978-1-4471-0347-9]Search in Google Scholar
[Colombo, A.F. and Kamey, B.W. (2002). Energy and costs of leaky pipes: Toward comprehensive picture, Journal of Water Resource Planning and Management 128(6): 441-450.10.1061/(ASCE)0733-9496(2002)128:6(441)]Search in Google Scholar
[Fujiwara, O. and Khang, D.B. (1990). A two-phase decomposition method for optimal design of looped water distribution networks, Water Resources Research 26(4): 539-549.10.1029/WR026i004p00539]Search in Google Scholar
[Houghtalen, R.J., Akan, A.O. and Hwang, N.H.C. (2010). Fundamentals of Hydraulic Engineering Systems, 4th Edn., Prentice Hall, Englewood Cliffs, NJ.]Search in Google Scholar
[Jung, D. and Lansey, K. (2015). Water distribution system burst detection using a nonlinear Kalman filter, Journal of Water Resources Planning and Management 141(5): 1-13.10.1061/(ASCE)WR.1943-5452.0000464]Search in Google Scholar
[Ku, W., Storer, R.H. and Georgakis, C. (1995). Disturbance detection and isolation by dynamic principal component analysis, Chemometrics and Intelligent Laboratory Systems 30: 179-196.10.1016/0169-7439(95)00076-3]Search in Google Scholar
[Łangowski, R. and Brdys, M.A. (2017). An interval estimator for chlorine monitoring in drinking water distribution systems under uncertain system dynamics, inputs and chlorine concentration measurement errors, International Journal of Applied Mathematics and Computer Science 27(2): 309-322, DOI: 10.1515/amcs-2017-0022.10.1515/amcs-2017-0022]Open DOISearch in Google Scholar
[Laucelli, D., Romano, M., Savic, D. and Giustolisi, O. (2016). Detecting anomalies in water distribution networks using EPR modelling paradigm, Journal of Hydroinformatics 18(3): 409-427.10.2166/hydro.2015.113]Search in Google Scholar
[Ko´scielny, J.M., Syfert, M., Rostek, K. and Sztyber, A. (2017). Fault isolability with different forms of the faults-symptoms relation, International Journal of Applied Mathematics and Computer Science 26(4): 815-826, DOI: 10.1515/amcs-2016-0058.10.1515/amcs-2016-0058]Open DOISearch in Google Scholar
[Moczulski, W., Wycz, R., Ciupke, K., Przystałka, P., Tomasik, P. and Wachla, D. (2016). A methodology of leakage detection and location in water distribution networks-The case study, Conference on Control and Fault Tolerant Systems SysTol, Barcelona, Spain, pp. 331-336.10.1109/SYSTOL.2016.7739772]Search in Google Scholar
[Montgomery, D.C. and Runger, G.C. (2014). Applied Statistics and Probability for Engineers, 6th Edn., Wiley, Hoboken, NJ. Mounce, S.R., Mounce, R.B., Jackson, T., Austin, J. and Boxall, J.B. (2014). Pattern matching and associative artificial neural networks for water distribution system time series data analysis, Journal of Hydroinformatics 16(3): 617-632.10.2166/hydro.2013.057]Search in Google Scholar
[Nowicki, A., Grochowski, M. and Duzinkiewicz, K. (2012). Data-driven models for fault detection using kernel PCA: A water distribution system case study, International Journal of Applied Mathematics and Computer Science 22(4): 939-949, DOI: 10.2478/v10006-012-0070-1.10.2478/v10006-012-0070-1]Open DOISearch in Google Scholar
[Olsson, G. (2006). Instrumentation, control and automation in the water industry-State-of-the-art and new challenges, Water Science and Technology 53(4-5): 1-16.10.2166/wst.2006.097]Search in Google Scholar
[Palau, C.V., Arregui, F.J. and Carlos, M. (2012). Burst detection in water networks using principal component analysis, Journal of Water Resources Planning and Management 138(1): 47-54.10.1061/(ASCE)WR.1943-5452.0000147]Search in Google Scholar
[Papoulis, A. (1991). Probability, Random Variables, and Stochastic Processes, 3rd Edn., McGraw-Hill, New York, NY.]Search in Google Scholar
[Quiñones-Grueiro, M., Verde, C. and Llanes-Santiago, O. (2017). Features of demand patterns for leak detection in water distribution networks, in C. Verde and L. Torres (Eds.), Modeling and Monitoring of Pipelines and Networks, Springer, Cham, Chapter 9, pp. 171-189.10.1007/978-3-319-55944-5_9]Search in Google Scholar
[Quiñones-Grueiro, M., Verde, C. and Prieto-Moreno, A. (2016). Leaks’ detection in water distribution networks with demand patterns, 3rd Conference on Control and Fault Tolerant Systems SysTol, Barcelona, Spain, pp. 313-318.10.1109/SYSTOL.2016.7739769]Search in Google Scholar
[Rato, T.J. and Reis, M.S. (2013). Defining the structure of DPCA models and its impact on process monitoring and prediction activities, Chemometrics and Intelligent Laboratory Systems 125: 74-86.10.1016/j.chemolab.2013.03.009]Search in Google Scholar
[Romano, M., Kapelan, Z. and Savi´c, D.A. (2010). Real-time leak detection in water distribution systems, Water Distribution Systems Analysis Conference, ASCE, Tucson, AZ, USA, pp. 1074-1082.]Search in Google Scholar
[Romano, M., Kapelan, Z. and Savic, D.A. (2013). Geostatistical techniques for approximate location of pipe burst events in water distribution systems, Journal of Hydroinformatics 15(3): 634-652.10.2166/hydro.2013.094]Search in Google Scholar
[Rossman, L.A. (2000). Epanet 2 User’s Manual, Technical report, United States Envionmental Protection Agency, http://www.epa.gov/nrmrl/wswrd/dw/epanet.html.]Search in Google Scholar
[Sanz, G., Pérez, R., Kapelan, Z., Savic, D. and Asce, A.M. (2015). Leak detection and localization through demand components calibration, Journal of Water Resources Planning and Management 142(2): 1-13.10.1061/(ASCE)WR.1943-5452.0000592]Search in Google Scholar
[Sedki, A. and Ouazar, D. (2012). Hybrid particle swarm optimization and differential evolution for optimal design of water distribution systems, Advanced Engineering Informatics 26(3): 582-591.10.1016/j.aei.2012.03.007]Search in Google Scholar
[Soldevila, A., Blesa, J., Tornil-Sin, S., Duviella, E., Fernandez-Canti, R.M. and Puig, V. (2016). Leak localization in water distribution networks using a mixed model-based/data-driven approach, Control Engineering Practice 55: 162-173.10.1016/j.conengprac.2016.07.006]Search in Google Scholar
[Soldevila, A., Fernandez-Canti, R.M., Blesa, J., Tornil-Sin, S. and Puig, V. (2017). Leak localization in water distribution networks using Bayesian classifiers, Journal of Process Control 55: 1-9.10.1016/j.jprocont.2017.03.015]Search in Google Scholar
[Wachla, D., Przystalka, P.and Moczulski, W. (2015). A method of leakage location in water distribution networks using artificial-neuro fuzzy system, IFAC-PapersOnLine 48(21): 1216-1223.10.1016/j.ifacol.2015.09.692]Search in Google Scholar
[Wang, J., Member, S., Chen, T., Member, S. and Huang, B. (2006). Cyclo-period estimation for discrete-time cyclo-stationary signals, IEEE Transactions on Signal Processing 54(1): 83-94.10.1109/TSP.2005.859237]Search in Google Scholar
[Wu, Y., Liu, S., Wu, X., Liu, Y. and Guan, Y. (2016). Burst detection in district metering areas using a data driven clustering algorithm, Water Research 100: 28-37.10.1016/j.watres.2016.05.016]Search in Google Scholar
[Yue, H.H. and Qin, S.J. (2001). Reconstruction-based fault identification using a combined index, Industrial & Engineering Chemistry Research 40(20): 4403-4414.10.1021/ie000141+]Search in Google Scholar
[Zhang, Q., Wu, Z.Y., Zhao, M., Qi, J., Huang, Y. and Zhao, H. (2016). Leakage zone identification in large-scale water distribution systems using multiclass support vector machines, Journal of Water Resources Planning and Management 142(11): 1-15.10.1061/(ASCE)WR.1943-5452.0000661]Search in Google Scholar
[Zhou, S.L., McMahon, T.A., Walton, A. and Lewis, J. (2002). Forecasting operational demand for an urban water supply zone, Journal of Hydrology 259(1-4): 189-202.10.1016/S0022-1694(01)00582-0]Search in Google Scholar