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A similarity-based inference engine for non-singleton fuzzy logic systems (2016)
Conference Proceeding
Wagner, C., Pourabdollah, A., McCulloch, J., John, R., & Garibaldi, J. M. (2016). A similarity-based inference engine for non-singleton fuzzy logic systems. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (316-323). https://doi.org/10.1109/FUZZ-IEEE.2016.7737703

In non-singleton fuzzy logic systems (NSFLSs) input uncertainties are modelled with input fuzzy sets in order to capture input uncertainty such as sensor noise. The performance of NSFLSs in handling such uncertainties depends both on the actual input... Read More about A similarity-based inference engine for non-singleton fuzzy logic systems.

Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems (2016)
Conference Proceeding
Aladi, J. H., Wagner, C., & Pourabdollah, A. (2016). Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems.

Most applications of both type-1 and type-2 fuzzy logic systems are employing singleton fuzzification due to its simplicity and reduction in its computational speed. However, using singleton fuzzification assumes that the input data (i.e., measuremen... Read More about Contrasting singleton type-1 and interval type-2 non-singleton type-1 fuzzy logic systems.

Improved Uncertainty Capture for Nonsingleton Fuzzy Systems (2016)
Journal Article
Pourabdollah, A., Wagner, C., Aladi, J. H., & Garibaldi, J. M. (2016). Improved Uncertainty Capture for Nonsingleton Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 24(6), 1513-1524. https://doi.org/10.1109/TFUZZ.2016.2540065

© 2016 IEEE. In nonsingleton fuzzy logic systems (NSFLSs), input uncertainties are modeled with input fuzzy sets in order to capture input uncertainty (e.g., sensor noise). The performance of NSFLSs in handling such uncertainties depends on both the... Read More about Improved Uncertainty Capture for Nonsingleton Fuzzy Systems.

Quality assessment of OpenStreetMap data using trajectory mining (2016)
Journal Article
Basiri, A., Jackson, M., Amirian, P., Pourabdollah, A., Sester, M., Winstanley, A., …Zhang, L. (2016). Quality assessment of OpenStreetMap data using trajectory mining. Geo-Spatial Information Scienc, 19(1), https://doi.org/10.1080/10095020.2016.1151213

OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions,... Read More about Quality assessment of OpenStreetMap data using trajectory mining.