Exploration of applying fuzzy logic for official statistics
نویسنده
چکیده
People are familiar with lingustic terms e.g. high response burden, low migration level, medium migration level which describe particular objects e.g. companies, territorial units. In research that includes these classes it is not easy to unambiguously create their boundaries. The fuzzy logic offers calculations with linguistic terms and approximate reasoning in order to solve data selection, dissemination and classification problems in a way that more resembles human logic. Selection of relevant entities from data sets can be more flexible, allowing examination of records that almost meet the given criteria, as well as those that clearly meet the criteria. Fuzzy classification directly employs expert knowledge by means of approximate reasoning and linguistic terms using fuzzy if-then rules in order to classify data into several classes, e.g. key objects, significant and insignificant objects.Websites with fuzzy logic could become more user friendly oriented in processes of data searching and selection. The basic equation, fuzzy greneralized logical condition (GLC) has been created and it could be extended in several ways to catch particular needs. Official statistics is a promising area to develop and implement the concept based on the fuzzy logic. Data sets have stored large amounts of quantitative and qualitative data that contain potentially valuable information. Illustrative example has been created in order to present applicability of the fuzzy logic and especially the created GLC on data from official statistics.
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