rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Modeling Conflict Dynamics with Spatio-temporal Data
  name:
    name part: Zammit-Mangion, Andrew.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Dewar, Michael.
    role:
      role term: author.
  name:
    name part: Kadirkamanathan, Visakan.
    role:
      role term: author.
  name:
    name part: Flesken, Anaïd.
    role:
      role term: author.
  name:
    name part: Sanguinetti, Guido.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VIII, 74 p. 13 illus., 1 illus. in color. online resource.
  abstract: This authored monograph presents the use of dynamic spatiotemporal modeling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. The authors use ideas from statistics, signal processing, and ecology, and provide a predictive framework which is able to assimilate data and give confidence estimates on the predictions. The book also demonstrates the methods on the WikiLeaks Afghan War Diary, the results showing that this approach allows deeper insights into conflict dynamics and allows a strikingly statistically accurate forward prediction of armed opposition group activity in 2010, based solely on data from preceding years. The target audience primarily comprises researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
  table of contents: Conflict Data Sets and Point Patterns -- Theory -- Modelling and Prediction in Conflict: Afghanistan.
  note: by Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaïd Flesken, Guido Sanguinetti.
  subject:
    topic: Physics
  subject:
    topic: Probabilities
  subject:
    topic: Mathematics
  subject:
    topic: Social sciences
  subject:
    topic: Sociophysics
  subject:
    topic: Econophysics
  subject:
    topic: Complexity, Computational
  subject:
    topic: Physics
  subject:
    topic: Socio- and Econophysics, Population and Evolutionary Models
  subject:
    topic: Mathematics in the Humanities and Social Sciences
  subject:
    topic: Complexity
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Signal, Image and Speech Processing
  classification: QC1-999
  classification: 621
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Applied Sciences and Technology
  identifier: 9783319010380
  identifier: http://dx.doi.org/10.1007/978-3-319-01038-0
  record info:
    record creation date: 130930
    record change date: 20151103121201.0
    record identifier: 978-3-319-01038-0