Advances in Fuzzy Systems

Fuzzy Methods and Approximate Reasoning in Geographical Information Systems


Publishing date
31 Jan 2014
Status
Published
Submission deadline
13 Sep 2013

1Università degli Studi di Napoli Federico II, Dipartimento di Architettura, via Toledo 402, 80134 Napoli, Italy

2Centre of Excellence IT4Innovations, Division University of Ostrava, Institute for Research and Applications of Fuzzy Modeling, 70103 Ostrava, Czech Republic

3Università degli Studi di Salerno, Dipartimento di Informatica, via ponte don Melillo, 84084 Fisciano, Italy


Fuzzy Methods and Approximate Reasoning in Geographical Information Systems

Description

A geographical information system (GIS) is a system used for storing, analyzing, and manipulating spatial data. GIS represents a spatial decision support system for decision makers in many fields as urban planning, transport network and infrastructure management, land use, geological analysis, earthquake forecasting, crime analysis, and disease analysis. Fuzzy logic is used by planners and experts in many disciplines involving uncertainty representation, qualitative spatial reasoning, and approximating problems as follows:

  • Rule management systems
  • Multicriteria decision analysis
  • Fuzzy spatial analysis
  • Reliability analysis
  • Spatial data mining

Indeed, many spatially defined entities and phenomena show a degree of vagueness or uncertainty that can be properly expressed using fuzzy sets and fuzzy inferences, for example, a spatial relationship of closeness by which we evaluate the pollution of source water determined from the presence of an industrial building. Heterogeneous and often unknown data quality greatly affects the reliability of the spatial analysis, and a fuzzy approach becomes tremendously necessary for evaluating this reliability. Moreover, fuzzy methods are used for implementing in a GIS environment spatial data mining algorithms as, for example, spatial clusters for hotspot analysis and regression models for location prediction.

We invite interested researchers to contribute with original articles concerning new approaches involving fuzzy sets and approximate reasoning strategies implemented in a GIS for representation, management, analysis, and exploration of spatial data as well. We are particularly interested in papers describing new approaches for dealing with uncertainty in the spatial data in which any fuzzy-logic-based model has been tested over application contexts and encapsulated in a GIS platform. Potential topics include, but are not limited to:

  • Fuzzy models for qualitative spatial reasoning
  • Fuzzy methods for spatial data reliability analysis
  • Fuzzy methods for multicriteria decision analysis in a GIS
  • Applications of fuzzy inference models for problem solving in a GIS
  • Applications of new fuzzy methods and algorithms for spatial data mining in a GIS
  • Applications of fuzzy clustering algorithms for hot spot analysis in a GIS

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/afs/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/afs/gis/ according to the following timetable:

Advances in Fuzzy Systems
 Journal metrics
Acceptance rate16%
Submission to final decision95 days
Acceptance to publication41 days
CiteScore2.200
Impact Factor-
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