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| Titel |
hydroPSO: A Versatile Particle Swarm Optimisation R Package for Calibration of Environmental Models |
| VerfasserIn |
M. Zambrano-Bigiarini, R. Rojas |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250068554
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| Zusammenfassung |
| Particle Swarm Optimisation (PSO) is a recent and powerful population-based stochastic
optimisation technique inspired by social behaviour of bird flocking, which shares similarities
with other evolutionary techniques such as Genetic Algorithms (GA). In PSO, however, each
individual of the population, known as particle in PSO terminology, adjusts its flying
trajectory on the multi-dimensional search-space according to its own experience
(best-known personal position) and the one of its neighbours in the swarm (best-known local
position). PSO has recently received a surge of attention given its flexibility, ease of
programming, low memory and CPU requirements, and efficiency. Despite these
advantages, PSO may still get trapped into sub-optimal solutions, suffer from swarm
explosion or premature convergence. Thus, the development of enhancements to the
“canonical” PSO is an active area of research. To date, several modifications to the
canonical PSO have been proposed in the literature, resulting into a large and dispersed
collection of codes and algorithms which might well be used for similar if not identical
purposes.
In this work we present hydroPSO, a platform-independent R package implementing
several enhancements to the canonical PSO that we consider of utmost importance to bring
this technique to the attention of a broader community of scientists and practitioners.
hydroPSO is model-independent, allowing the user to interface any model code with
the calibration engine without having to invest considerable effort in customizing
PSO to a new calibration problem. Some of the controlling options to fine-tune
hydroPSO are: four alternative topologies, several types of inertia weight, time-variant
acceleration coefficients, time-variant maximum velocity, regrouping of particles
when premature convergence is detected, different types of boundary conditions and
many others. Additionally, hydroPSO implements recent PSO variants such as:
Improved Particle Swarm Optimisation (IPSO), Fully Informed Particle Swarm (FIPS),
and weighted FIPS (wFIPS). Finally, an advanced sensitivity analysis using the
Latin Hypercube One-At-a-Time (LH-OAT) method and user-friendly plotting
summaries facilitate the interpretation and assessment of the calibration/optimisation
results.
We validate hydroPSO against the standard PSO algorithm (SPSO-2007) employing five
test functions commonly used to assess the performance of optimisation algorithms.
Additionally, we illustrate how the performance of the optimization/calibration engine is
boosted by using several of the fine-tune options included in hydroPSO. Finally, we show
how to interface SWAT-2005 with hydroPSO to calibrate a semi-distributed hydrological
model for the Ega River basin in Spain, and how to interface MODFLOW-2000 and
hydroPSO to calibrate a groundwater flow model for the regional aquifer of the Pampa del
Tamarugal in Chile. We limit the applications of hydroPSO to study cases dealing
with surface water and groundwater models as these two are the authors’ areas of
expertise. However, based on the flexibility of hydroPSO we believe this package can be
implemented to any model code requiring some form of parameter estimation. |
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