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Modeling Words for Qualitative Distance Based on Interval Type-2 Fuzzy Sets

1,* and 2
School of Geographic and Environmental Sciences, Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(8), 291;
Received: 22 May 2018 / Revised: 10 June 2018 / Accepted: 20 July 2018 / Published: 24 July 2018
PDF [2717 KB, uploaded 24 July 2018]


Modeling qualitative distance words is important for natural language understanding, scene reconstruction and many decision support systems (DSSs) based on a geographic information system (GIS). However, it is difficult to establish the relationship between qualitative distance words and quantitative distance for special applications since the meanings of these words are influenced by both subjective and objective factors. Some existing methods are reviewed, and the Hao–Mendel approach (HMA) is improved to model qualitative distance words for four travel modes by using interval type-2 fuzzy sets (IT2 FSs), aiming at addressing the individual and interpersonal uncertainty among qualitative distance words. The area of the footprint of uncertainty (FOU), fuzziness (entropy), and variance are adopted to measure the uncertainties of qualitative distance words. The experimental results show that the improved HMA algorithm is better than the original HMA algorithm and can be used in spatial information retrieval and GIS-based DSSs. View Full-Text
Keywords: uncertainty; qualitative distance words; spatial relations; IT2 FS uncertainty; qualitative distance words; spatial relations; IT2 FS

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Guo, J.; Du, S. Modeling Words for Qualitative Distance Based on Interval Type-2 Fuzzy Sets. ISPRS Int. J. Geo-Inf. 2018, 7, 291.

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