کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6733740 504061 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Data mining in building automation system for improving building operational performance
ترجمه فارسی عنوان
داده کاوی در سیستم اتوماسیون ساختمان برای بهبود عملکرد عملیاتی ساختمان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Today's building automation system (BAS) provides us with a tremendous amount of data on actual building operation. Buildings are becoming not only energy-intensive, but also information-intensive. Data mining (DM) is an emerging powerful technique with great potential to discover hidden knowledge in large data sets. This study investigates the use of DM for analyzing the large data sets in BAS with the aim of improving building operational performance. An applicable framework for mining BAS database is proposed. The framework is implemented to mine the BAS database of the tallest building in Hong Kong. After data preparation, clustering analysis is performed to identify the typical power consumption patterns of the building. Then, association rule mining is adopted to unveil the associations among power consumptions of major components in each cluster. Lastly, post-mining is conducted to interpret the rules. 457 rules are obtained in association rule mining, of which the majority can be easily deduced from domain knowledge and hence be ignored in this study. Four of the rules are used for improving building performance. This study shows that DM techniques are valuable for knowledge discovery in BAS database; however, solid domain knowledge is still needed to apply the knowledge discovered to achieve better building operational performance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 75, June 2014, Pages 109-118
نویسندگان
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