abstract: A challenge in computational modeling of complex geospatial systems is the
  amount of time and resources required to tune a set of parameters that reproduces
  the observed patterns of phenomena of being modeled. Well-tuned parameters are necessary
  for models to reproduce real-world multi-scale space-time patterns, but calibration
  is often computationally-intensive and time-consuming. Particle Swarm Optimization
  (PSO) is a swarm intelligence optimization algorithm that has found wide use for
  complex optimization including non-convex and noisy problems. In this study, we
  propose to use PSO for calibrating parameters in spatially explicit agent-based
  models (ABMs). We use a spatially explicit ABM of influenza transmission based in
  Miami, Florida, USA as a case study. Further, we demonstrate that a standard implementation
  of PSO can be used out-of-the-box to successfully calibrate models and out-performs
  Monte Carlo in terms of optimization and efficiency. The notebook is designed to
  teach you about Particle Swarm Optimization (PSO) and how you can use it for parameter
  optimization.
authors:
- email: michels9@illinois.edu
  family-names: Michels
  given-names: Alexander
- affiliation: Kongju National University
  email: geokang@kongju.ac.kr
  family-names: Kang
  given-names: Jeon-Young
- affiliation: University of Illinois Urbana-Champaign
  email: shaowen@illinois.edu
  family-names: Wang
  given-names: Shaowen
cff-version: 1.2.0
identifiers:
- type: url
  value: https://www.comses.net/codebases/b136ee71-22e7-410f-b810-1b39525f9919/releases/1.0.0/
keywords:
- agent-based model (abm)
- cybergis
- model calibration
- particle swarm
license: MIT
message: If you use this software, please cite it using the metadata from this file.
repository-code: https://github.com/cybergis/PSONotebook
title: Particle Swarm Optimization for Calibration in Spatially Explicit Agent-Based
  Modeling
type: software
url: https://www.comses.net/codebases/b136ee71-22e7-410f-b810-1b39525f9919/releases/1.0.0/
version: 1.0.0
