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: Decision Aid Models for Disaster Management and Emergencies
  name:
    name part: Vitoriano, Begoña.
    role:
      role term: editor.
  name:
    name part: Montero, Javier.
    role:
      role term: editor.
  name:
    name part: Ruan, Da.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: fr
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XV, 325 p. online resource.
  abstract: Disaster management is a process or strategy that is implemented when any type of catastrophic event takes place. The process may be initiated when anything threatens to disrupt normal operations or puts the lives of human beings at risk. Governments on all levels as well as many businesses create some sort of disaster plan that make it possible to overcome the catastrophe and return to normal function as quickly as possible. Response to natural disasters (e.g., floods, earthquakes) or technological disaster (e.g., nuclear, chemical) is an extreme complex process that involves severe time pressure, various uncertainties, high non-linearity and many stakeholders. Disaster management often requires several autonomous agencies to collaboratively mitigate, prepare, respond, and recover from heterogeneous and dynamic sets of hazards to society. Almost all disasters involve high degrees of novelty to deal with most unexpected various uncertainties and dynamic time pressures. Existing studies and approaches within disaster management have mainly been focused on some specific type of disasters with certain agency oriented. There is a lack of a general framework to deal with similarities and synergies among different disasters by taking their specific features into account. This book provides with various decisions analysis theories and support tools in complex systems in general and in disaster management in particular. The book is also generated during a long-term preparation of a European project proposal among most leading experts in the areas related to the book title. Chapters are evaluated based on quality and originality in theory and methodology, application oriented, relevance to the title of the book.
  table of contents: On the Use of Information in Humanitarian Operations -- Decision Aid Models and Systems for Humanitarian Logistics. A Survey -- Uncertainty in Humanitarian Logistics for Disaster Management -- Fuzzy inference systems for disaster response -- Security Based Operation in Container Line Supply Chain -- A Linguistic-Valued Information Processing Method for Fuzzy Risk Analysis -- A Belief Rule-Based Generic Risk Assessment Framework -- Fuzzy semantics in closed domain question answering -- Decision Making with Extensions of Fuzzy Sets -- Classification of Disasters and Emergencies under Bipolar Knowledge Representation -- A Network Transshipment Model for Planning Humanitarian Relief Operations after a Natural Disaster -- A Travel Behaviour Study through Learning and Clustering of Fuzzy Cognitive Maps -- Fire and explosion safety assessment in container line supply chain -- A Human Situation Awareness Support System to Avoid Technological Disasters.
  note: edited by Begoña Vitoriano, Javier Montero, Da Ruan.
  subject:
    topic: Computer science
  subject:
    topic: Business
  subject:
    topic: Management science
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Computer simulation
  subject:
    topic: Application software
  subject:
    topic: Computer Science
  subject:
    topic: Simulation and Modeling
  subject:
    topic: Computer Applications
  subject:
    topic: Operation Research/Decision Theory
  subject:
    topic: Business and Management, general
  classification: QA76.9.C65
  classification: 003.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Atlantis Computational Intelligence Systems, 7
  identifier: 9789491216749
  identifier: http://dx.doi.org/10.2991/978-94-91216-74-9
  record info:
    record creation date: 130125
    record change date: 20151204191044.0
    record identifier: 978-94-91216-74-9