Armando Segatori

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In this contribution, we describe the SMARTY project. The project is funded by the Tuscany Region and aims to develop innovative services for sustainable transport and mobility in smart cities. These services are based on data collected by environmental and social sensors: such data are pre-processed and analysed by data mining techniques for determining(More)
Associative classifiers have proven to be very effective in classification problems. Unfortunately, the algorithms used for learning these classifiers are not able to adequately manage big data because of time complexity and memory constraints. To overcome such drawbacks, we propose a distributed association rule-based classification scheme shaped according(More)
In urban areas, finding a convenient place for car parking may determine a significant waste of energy, as well as environmental pollution. The introduction of proper software tools can indeed contribute to limit the environmental impact of inefficient car parking. By making use of a mobile application and a corresponding adequate information system, it is(More)
Fuzzy rule-based models have been extensively used in regression problems. Besides high accuracy, one of the most appreciated characteristics of these models is their interpretability, which is generally measured in terms of complexity. Complexity is affected by the number of features used for generating the model: the lower the number of features, the(More)