{"refrec":{"BRefID":323299,"RR":"<b>De Mol, R.; De Tré, G.</b> (2018). Applying suitability distributions in a geological context, <b><i>in</i></b>: Medina, J. <i>et al.</i> <i>Information processing and management of uncertainty in knowledge-based systems. Theory and foundations.</i> pp. 278-288. <a href=\"https://dx.doi.org/10.1007/978-3-319-91473-2_24\" target=\"_blank\">https://dx.doi.org/10.1007/978-3-319-91473-2_24</a>","BEntID":316771,"PublicFlag":1,"CheckedFlag":1,"wosflag":0,"vabbflag":0,"RefStringPartII":", <b><i>in</i></b>: Medina, J. <i>et al.</i> <i>Information processing and management of uncertainty in knowledge-based systems. Theory and foundations.</i> pp. 278-288. <a href=\"https://dx.doi.org/10.1007/978-3-319-91473-2_24\" target=\"_blank\">https://dx.doi.org/10.1007/978-3-319-91473-2_24</a>","DocTypID":17,"DocType":"Book chapters","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"De Mol, R.; De Tré, G.","OrigTitleTranslFlag":0,"Authorstringtrunc":"De Mol, R.; De Tré, G.","Englishabstract":"Some industrial purposes require specific marine resources. Companies rely on information from resource models to decide where to go and what the cost will be to perform the required extractions. Such models, however, are typical examples of imprecise data sets wherein most data is estimated rather than measured. This is especially true for marine resource models, for which acquiring real data samples is a long and costly endeavor. Consequently, such models are largely computed by interpolating data from a small set of measurements. In this paper, we discuss how we have applied fuzzy set theory on a real data set to deal with these issues. It is further explained how the resulting fuzzy model can be queried so it may be used in a decision making context. To evaluate queries, we use a novel preference modeling and evaluation technique specifically suited for dealing with uncertain data, based on suitability distributions. 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