کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6695824 1428275 2018 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Analysing real world data streams with spatio-temporal correlations: Entropy vs. Pearson correlation
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
Analysing real world data streams with spatio-temporal correlations: Entropy vs. Pearson correlation
چکیده انگلیسی
Smart Cities use different Internet of Things (IoT) data sources and rely on big data analytics to obtain information or extract actionable knowledge crucial for urban planners for efficiently use and plan the construction infrastructures. Big data analytics algorithms often consider the correlation of different patterns and various data types. However, the use of different techniques to measure the correlation with smart cities data and the exploitation of correlations to infer new knowledge are still open questions. This paper proposes a methodology to analyse data streams, based on spatio-temporal correlations using different correlation algorithms and provides a discussion on co-occurrence vs. causation. The proposed method is evaluated using traffic data collected from the road sensors in the city of Aarhus in Denmark.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automation in Construction - Volume 88, April 2018, Pages 87-100
نویسندگان
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