Fuzzy Geometric Relations to Represent Hierarchical Spatial Information
نویسندگان
چکیده
A model to represent spatial information is presented in this paper. It is based on fuzzy constraints represented as fuzzy geometric relations that can be hierarchically structured. The concept of spatial template is introduced to capture the idea of interrelated objects in two dimensional space. The representation model is used to specify imprecise or vague information consisting in relative locations and orientations of template objects. It is shown in this paper how a template represented by this model can be matched against a crisp situation to recognize a particular instance of this template. Furthermore, the proximity measure (fuzzy measure) between the instance and the template is worked out this measure can be interpreted as a degree of similarity. In this context, template recognition can be viewed as a case of fuzzy pattern recognition. The results of this work have been implemented and applied to a complex military problem from which this work originated.
منابع مشابه
مدلسازی روابط توپولوژیک سه بعدی فازی در محیط GIS
Nowadays, geospatial information systems (GIS) are widely used to solve different spatial problems based on various types of fundamental data: spatial, temporal, attribute and topological relations. Topological relations are the most important part of GIS which distinguish it from the other kinds of information technologies. One of the important mechanisms for representing topological relations...
متن کاملUncertainty analysis of hierarchical granular structures for multi-granulation typical hesitant fuzzy approximation space
Hierarchical structures and uncertainty measures are two main aspects in granular computing, approximate reasoning and cognitive process. Typical hesitant fuzzy sets, as a prime extension of fuzzy sets, are more flexible to reflect the hesitance and ambiguity in knowledge representation and decision making. In this paper, we mainly investigate the hierarchical structures and uncertainty measure...
متن کاملInterpreting the Fuzzy Semantics of Natural-Language Spatial Relation Terms with the Fuzzy Random Forest Algorithm
Naïve Geography, intelligent geographical information systems (GIS), and spatial data mining especially from social media all rely on natural-language spatial relations (NLSR) terms to incorporate commonsense spatial knowledge into conventional GIS and to enhance the semantic interoperability of spatial information in social media data. Yet, the inherent fuzziness of NLSR terms makes them chall...
متن کاملScene Learning, Recognition and Similarity Detection in a Fuzzy Ontology via Human Examples
This paper introduces a Fuzzy Logic framework for scene learning, recognition and similarity detection, where scenes are taught via human examples. The framework allows a robot to: (i) deal with the intrinsic vagueness associated with determining spatial relations among objects; (ii) infer similarities and dissimilarities in a set of scenes, and represent them in a hierarchical structure repres...
متن کاملMedical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations
Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different crite...
متن کامل