scholarly journals A fuzzy approach for determining the cognitive spatial location of an object in geographical information system

2021 ◽  
Vol 6 (9 (114)) ◽  
pp. 24-31
Author(s):  
Svitlana Kuznichenko ◽  
Iryna Buchynska
Keyword(s):  
Information System ◽  
Natural Language ◽  
Text Message ◽  
Fuzzy Model ◽  
Spatial Location ◽  
Spatial Relations ◽  
Spatial Knowledge ◽  
Geographical Information ◽  
Linguistic Variables ◽  
Fuzzy Approach

The work is devoted to the problem of interpretation of fuzzy semantics of cognitive descriptions of spatial relations in natural language and their visualization in a geographic information system (GIS). The solution to the problem of determining the fuzzy spatial location of an object based on vague descriptions of the observer in natural language is considered. The task is relevant in critical situations when there is no way to report the exact coordinates of the observed object, except by describing its location relative to the observer itself. Such a situation may be the result of a crime, terrorist act or natural disaster. An observer who finds itself at the scene transmits a text message, which is a description of the location of the object or place (for example, the crime scene, the location of dangerous objects, the crash site). The semantics of the spatial location of the object can be further extracted from the text message. The proposed fuzzy approach is based on the formalization of the observer's phrases, with which it can describe spatial relations, in the form of a set of linguistic variables that determine the direction and distance to the object. Examples of membership functions for linguistic variables are given. The spatial knowledge base is built on the basis of the phrases of observers and their corresponding fuzzy regions. Algorithms for constructing cognitive regions in GIS have been developed. Methods of their superposition to obtain the final fuzzy location of the object are proposed. An example of the implementation of a fuzzy model for identifying cognitive regions based on vague descriptions of several observers, performed using developed Python scripts integrated into ArcGIS 10.5, is considered.

BIM and Geospatial Information Systems

2010 ◽  
pp. 483-500 ◽  
Author(s):  
Ewan Peters
Keyword(s):  
Information System ◽  
Information Systems ◽  
Data Storage ◽  
Spatial Location ◽  
Geographical Information ◽  
Geospatial Information ◽  
Building Information ◽  
The Common ◽  
Construction Operation ◽  
Geospatial Information Systems

Historically and traditionally, location based information merely represents a feature’s location in a real world setting. Advances in information technology (IT) and data collection techniques have revolutionised the Geographical Information System or Geospatial Information Systems (GIS) industry. The relatively recent explosion in data storage and processing capabilities has led to more detailed and accurate data being collected. This provides a far greater data rich environment and more opportunities for exploiting this information. It is not enough to only know where something is. Questions like but what is it, what’s nearby and what are the associated attributes’ are more relevant now. A data rich Geospatial Information System allows for detailed spatial (location based) queries to be performed to explore and analyse these geographical relationships. In parallel to this information explosion, the built environment has started to embrace this revolution. In essence, a building is a component of a larger group of features which is linked by infrastructure and other elements to create a holistic system. The common factors which connect this system together all have an associated location. When viewing a building in isolation it is clear that it is made up of a number of different individual features. Information about these features is a key part to its design, construction, operation and maintenance. The term (BIM) Building Information Modelling refers to the information system which is developed to manage built features. Of course a building doesn’t float in space; it is closely related to other features and infrastructure. This chapter will explore the value of integrating BIM and Geospatial Information Systems into a single system, why this is important, and how this can be achieved.

scholarly journals Fuzzy Approach to Short-Term Youth Unemployment Forecast

2020 ◽  
Vol 73 ◽  
pp. 01007
Author(s):  
Simona Hašková
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Model ◽  
Youth Unemployment ◽  
Statistical Prediction ◽  
Inference Rules ◽  
Linguistic Variables ◽  
Fuzzy Approach ◽  
Short Term ◽  
Prediction Task ◽  
Macroeconomic Indicators

The practical output of the paper is the prediction of the percentage of the short-term youth unemployment in the following two consecutive years. For this purpose, the non-traditional fuzzy model of the relevant prediction task is formulated in its theoretical-methodological part, which is subsequently applied in the application part. By means of the exact tools of the fuzzy approach (fuzzy sets and inference rules for manipulation with them), the synergy, uncertainty and complexity of the values (terms) of vaguely defined linguistic variables of an economic-psychological nature represented by sets of selected macroeconomic indicators is reflected. Despite the fact that the results of the fuzzy prediction are not significantly different from the results of conventional statistical prediction, the demonstration of the approach of the case of knowledgeable expertise to the choice of the relevant fuzzy sets and the formulation of the set of inference rules can be considered as a secondary benefit.

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