title: Using a Combined Platform of Swarm Intelligence Algorithms and GIS to Provide Land Suitability Maps for Locating Cardiac Rehabilitation Defibrillators.
abstract: BACKGROUND
  Cardiac arrest is a condition in which the heart is completely stopped and is not pumping any blood. Although most cardiac arrest cases are reported from homes or hospitals, about 20% occur in public areas. Therefore, these areas need to be investigated in terms of cardiac arrest incidence so that places of high incidence can be identified and cardiac rehabilitation defibrillators installed there.
  
  
  METHODS
  In order to investigate a study area in Petersburg, Pennsylvania State, and to determine appropriate places for installing defibrillators with 5-year period data, swarm intelligence algorithms were used. Moreover, the location of the defibrillators was determined based on the following five evaluation criteria: land use, altitude of the area, economic conditions, distance from hospitals and approximate areas of reported cases of cardiac arrest for public places that were created in geospatial information system (GIS).
  
  
  RESULTS
  The A-P HADEL algorithm results were more precise about 27.36%. The validation results indicated a wider coverage of real values and the verification results confirmed the faster and more exact optimization of the cost function in the PSO method.
  
  
  CONCLUSIONS
  The study findings emphasize the necessity of applying optimal optimization methods along with GIS and precise selection of criteria in the selection of optimal locations for installing medical facilities because the selected algorithm and criteria dramatically affect the final responses. Meanwhile, providing land suitability maps for installing facilities across hot and risky spots has the potential to save many lives.
authors.affiliation: GIS Dept., K.N.Toosi University of Technology, Tehran, Iran.
authors.forename: Neda
authors.initials: N
authors.lastname: Kaffash-Charandabi
authors.affiliation: GIS Dept., K.N.Toosi University of Technology, Tehran, Iran ; Dept. of Geoinformatic Eng., Inha University, Incheon, South Korea.
authors.forename: Abolghasem
authors.initials: A
authors.lastname: Sadeghi-Niaraki
authors.affiliation: U-Healthcare Center, Gachon University, Gil Hospital, Incheon, South Korea.
authors.forename: Dong-Kyun
authors.initials: DK
authors.lastname: Park
keywords: ACO; Cardiac rehabilitation; Location; Optimization methods; PSO