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Marco Franchini   Professor  University Educator/Researcher 
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Marco Franchini published an article in July 2018.
Top co-authors See all
José A. Pons

294 shared publications

Universidad Autónoma de Barcelona Departamento de Química Bellaterra, Barcelona Spain

James P. Di Santo

225 shared publications

Innate Immunity Unit, Institut Pasteur, Paris, France

D. Savic

210 shared publications

Full Professor, Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, Univ. of Exeter, North Park Rd., Exeter EX4 4QF, UK

M. Ackermann

175 shared publications

Department of Mental Health and Psychiatry, University Hospitals of Geneva, Geneva, Switzerland

Aurel Perren

149 shared publications

Institute of Pathology, University of Bern, Bern, Switzerland

Publication Record
Distribution of Articles published per year 
(1970 - 2018)
Total number of journals
published in
Publications See all
Article 0 Reads 0 Citations From Water Consumption Smart Metering to Leakage Characterization at District and User Level: The GST4Water Project Chiara Luciani, Francesco Casellato, Stefano Alvisi, Marco F... Published: 30 July 2018
Proceedings, doi: 10.3390/proceedings2110675
DOI See at publisher website ABS Show/hide abstract
This paper presents some of the results achieved within the framework of the GST4Water project concerning the development of a real time monitoring and processing system for water consumption at individual user level. The system is based on the most innovative technologies proposed by the ICT sector and allows for receiving consumption data sent by a generic smart-meter installed in an user’s house and transfer them to a cloud platform. Here, the consumption data are stored and processed in order to characterize leakage at district meter area (DMA) and at individual user level. Finally, the processed data, on the one hand, are returned to the Water Utility and can be used for billing, on the other hand, they provide frequent feedback to the user thus gaining full awareness of his consumption behaviour.
Article 0 Reads 0 Citations Editorial: Efficient water systems management Vasilis Kanakoudis, Marco Franchini Published: 29 November 2017
Journal of Hydroinformatics, doi: 10.2166/hydro.2017.001
DOI See at publisher website
Article 3 Reads 4 Citations Unsteady Flow Modeling of Pressure Real-Time Control in Water Distribution Networks Enrico Creaco, Alberto Campisano, Marco Franchini, Carlo Mod... Published: 01 September 2017
Journal of Water Resources Planning and Management, doi: 10.1061/(ASCE)WR.1943-5452.0000821
DOI See at publisher website
Article 0 Reads 0 Citations A robust approach based on time variable trigger levels for pump control Stefano Alvisi, Marco Franchini Published: 05 August 2017
Journal of Hydroinformatics, doi: 10.2166/hydro.2017.141
DOI See at publisher website
Article 3 Reads 4 Citations A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain Francesca Gagliardi, Stefano Alvisi, Zoran Kapelan, Marco Fr... Published: 12 July 2017
Water, doi: 10.3390/w9070507
DOI See at publisher website ABS Show/hide abstract
This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods), were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.
Article 3 Reads 0 Citations Estimating discharge in drainage channels through measurements of surface velocity alone: A case study G. Farina, M. Bolognesi, S. Alvisi, M. Franchini, A. Pellegr... Published: 01 April 2017
Flow Measurement and Instrumentation, doi: 10.1016/j.flowmeasinst.2017.02.006
DOI See at publisher website