0000000000173791

AUTHOR

Ferdinando Di Martino

showing 4 related works from this author

Spatiotemporal hotspots analysis for exploring the evolution of diseases: An application to oto-laryngopharyngeal diseases

2013

Abstract View references (14) This paper presents a spatiotemporal analysis of hotspot areas based on the Extended Fuzzy C-Means method implemented in a geographic information system. This method has been adapted for detecting spatial areas with high concentrations of events and tested to study their temporal evolution. The data consist of georeferenced patterns corresponding to the residence of patients in the district of Naples (Italy) to whom a surgical intervention to the oto-laryngopharyngeal apparatus was carried out between the years 2008 and 2012

lcsh:Computer softwareGeographic information systemControl and OptimizationArticle Subjectbusiness.industrySpatiotemporal AnalysisComputational Mathematics Fuzzy C-Means disease analysis.disease analysisComputational Mathematicslcsh:QA76.75-76.765GeographyFuzzy C-MeansControl and Systems EngineeringGeoreferenceHotspot (geology)lcsh:Electrical engineering. Electronics. Nuclear engineeringbusinesslcsh:TK1-9971CartographyDemography
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A fuzzy-based tool for modelization and analysis of the vulnerability of aquifers: a case study

2005

Abstract A fuzzy-based tool, called FUZZY-SRA (Fuzzy Spatial Reliability Analysis), is used for realizing a more “reliable” study of the values of the final parameters concerning the vulnerability of aquifers located in the territory of Cava de' Tirreni, city in the district of Salerno (Italy). The SINTACS method is adopted for evaluating the involved parameters and these evaluations are modelled from attributes represented from triangular fuzzy numbers which supply the overall final information if combined with suitable algebraic operations. The tool FUZZY-SRA is implemented inside a GIS (Geographical Information Systems) software.

geographygeography.geographical_feature_categoryOperations researchbusiness.industryComputer scienceGeographic Information SystemApplied MathematicsSpatial analysisAquiferFuzzy logicTheoretical Computer ScienceReliability engineeringSoftwareArtificial IntelligenceAlgebraic operationGeographic Information SystemsInformation systemFuzzy numberbusinessFuzzy numberSoftwareReliability (statistics)Vulnerability (computing)International Journal of Approximate Reasoning
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Fuzzy Methods and Approximate Reasoning in Geographical Information Systems

2014

This issue has been dedicated to the usage of fuzzy logic in the context of Geographical Information Systems (GIS) and were receveid the following papers whose contents are described below: - in the paper of A. Hofmann, S. Hoskova-Mayerova, and V. Talhofer, the authors use a GIS tool which is useful to study the influence of geographic and climatic factors on the terrain passability of armed forces and the Integrated Rescue System. - In the first paper of S. Sessa and F. Di Martino, the authors propose the usage of the well known Extended Gustafson-Kessel clustering method, encapsulated in a GIS tool, for detecting hotspots in spatial analysis. The data consist of geo-referenced patterns co…

lcsh:Computer softwareReasoning systemControl and OptimizationFuzzy classificationNeuro-fuzzyArticle SubjectComputer sciencebusiness.industrySPATIAL ANALYSISModel-based reasoningGISFuzzy logicComputational Mathematicslcsh:QA76.75-76.765Control and Systems EngineeringInformation systemFuzzy set operationsApproximate reasoningArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringbusinessFUZZY SETSlcsh:TK1-9971Advances in Fuzzy Systems
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Fuzzy Systems Based on Multispecies PSO Method in Spatial Analysis

2012

We present a method by using the hierarchical cluster-based Multispecies particle swarm optimization to generate a fuzzy system of Takagi-Sugeno-Kang type encapsulated in a geographical information system considered as environmental decision support for spatial analysis. We consider a spatial area partitioned in subzones: the data measured in each subzone are used to extract a fuzzy rule set of above mentioned type. We adopt a similarity index (greater than a specific threshold) for comparing fuzzy systems generated for adjacent subzones.

fuzzy systemlcsh:Computer softwareDecision support systemControl and OptimizationFuzzy rulespatial analysisArticle SubjectParticle swarm optimizationFuzzy control systemcomputer.software_genreHierarchical clusteringSet (abstract data type)Computational Mathematicslcsh:QA76.75-76.765Similarity (network science)Control and Systems EngineeringInformation systemData mininglcsh:Electrical engineering. Electronics. Nuclear engineeringmultispecies PSOcomputerlcsh:TK1-9971MathematicsAdvances in Fuzzy Systems
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