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Comparison of Fuzzy AHP Algorithms for Land Suitability Assessment

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Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

Weighted Linear Combination (WLC) is one of the most popular methods for Multiple Criteria Decision-making (MCDM) in the field of geoinformatics. A typical utilization of WLC is in land suitability assessment and optimal location detection. The application of WLC requires the determination of weights for each criterion used in the MCDM problem. In this paper, we focus on a fuzzy Analytical Hierarchy Process (AHP) which is based on pairwise comparisons of criterion importance and, unlike the classic (crisp) AHP, it can contain uncertainty. This allows the user to include imprecise or incomplete knowledge in an MCDM problem. The theoretical part of the paper briefly describes fuzzy AHP and provides the necessary mathematical background. The practical part of the contribution is focused on testing two algorithms for weight determination in fuzzy AHP—the extent analysis method and a method based on constrained fuzzy arithmetic. The methods are described in terms of the amount of uncertainty in the result, the resulting value, and overall appropriateness. A four level fuzzy AHP problem containing one main goal, three criteria and twenty-four subcriteria is solved as a case study using both methods. Based on the results obtained, the recommendations for fuzzy AHP utilization in spatial suitability assessment are made.

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Acknowledgements

The paper was supported by Internal Grant Agency of Palacký University Olomouc (project IGA_PrF_2016_008—Advanced monitoring, spatial analysis and visualization of urban landscape) and by the ERASMUS + project no. 2016-1-CZ01-KA203-024040.

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Correspondence to Jan Caha .

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Caha, J., Burian, J. (2018). Comparison of Fuzzy AHP Algorithms for Land Suitability Assessment. In: Ivan, I., Horák, J., Inspektor, T. (eds) Dynamics in GIscience. GIS OSTRAVA 2017. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-61297-3_3

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