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An Expert GIS-Based ANP-OWA Decision Making Framework for Tourism Development Site Selection
Author(s) -
Khalid A. Eldrandaly,
Mohammed A. AL-Amari
Publication year - 2014
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2014.07.01
Subject(s) - computer science , selection (genetic algorithm) , tourism , site selection , fuzzy logic , process (computing) , geographic information system , analytic network process , operations research , data mining , multiple criteria decision analysis , analytic hierarchy process , artificial intelligence , mathematics , geography , political science , law , remote sensing , archaeology , operating system
—The selection of a tourism development site involves a complex array of decision criteria that may have interdependence relationships within and between them. In the process of finding the optimum location that meet desired conditions, the analyst is challenged by the tedious manipulation of spatial data and the management of multiple decision-making criteria. This paper presents a novel decision making framework in which expert systems (ES), and geographic information systems–based multicriteria evaluation techniques (Analytical Network Process and fuzzy quantifiers-guided ordered weighted averaging operators (GIS-based ANP-OWA)) are integrated systematically to facilitate the selection of suitable sites for building new tourism facilities. First, ES is used for recommending the proper site selection criteria and their interdependence relationships. Then, the GIS-based ANP-OWA is used to perform the spatial data analysis necessary to generate a wide range of possible candidate sites’ scenarios taking into accounts both the interdependence relationships between sitting criteria and the level of risk the decision-makers wish to assume in their multicriteria evaluation. A typical case study is presented to demonstrate the application of the proposed decision making framework.

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