Particle swarm optimization for calculating pressure on water distribution systems

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Lala Septem Riza, Azhari Fathurachman Azmi, Waslaluddin, Eka Fitrajaya Rahman, Kuntjoro Adji Sidarto

2016 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9712 LNCS Article Cited by 1 SDG 6 Quartile

Abstract

Flow assurance, aimed to ensure the availability of water flow rate and the sufficiency of pressure on each customer, is one of objectives that should be achieved by water supplying companies. An essential step before dealing with it is to predict pressure distribution on each node. Using the analogy of Kirchoff’s Law for the electrical current to the flow of water in pipelines, a non-linear equation system involving fluid dynamics modeling is constructed and used for determining pressure distribution. It is obvious that the system is not a simple one since it contains many non-linear equations expressing the complexity of the network. In this study, we implement Particle Swarm Optimization (PSO) to solve the system by transforming a root-finding task into an optimization problem. Finally, we present a case study using Hanoi network along with a result compared with EPANET, Firefly Algorithm (FA), and a combination of Genetic Algorithm (GA) and Newton’s method. © Springer International Publishing Switzerland 2016.

Affiliations

Universitas Pendidikan Indonesia, Setiabudhi 229, Bandung, Indonesia; Institut Teknologi Bandung, Ganesha 10, Bandung, Indonesia

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