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Big data-informed energy efficiency assessment of China industry sectors based on K-means clustering
ارزیابی کارآیی انرژی ارزیابی انرژی در بخش های صنعتی چین بر اساس الگوریتم K-means خوشه بندی-2018 The regional energy management body has a large amount of regional industrial companies’ energy
consumption data. It can evaluate the energy utilization of listed regional industrial companies based on
the total data and, then, find the key points for understanding the resources usage patterns, identifying
the problematic companies, and establishing good energy consumption practices. This paper reviews the
research progress on big data analysis and industrial energy efficiency evaluation and focuses on the
energy efficiency evaluation methods based on energy consumption process analysis and big data mining
approach. Based on K-means and multi-dimensional association rules algorithm, to analyze the charac
teristics of regional energy consumption in different industries and companies, we cluster single industry
in K-means and finding their levels of water and energy consumption. This classification provided us a
reference point to identify the industries and companies to focus on and locate the bad consumption
practices and environmental performance. Then, multi-dimensional association rules are used to find the
correlation of processes, companies and energy efficiency to guide the energy conservation in regional
energy monitor. The output of our research is a working Big Data analytics platform and the results
generated from advance analytics techniques applied specifically to solve regional energy efficiency
problems.
Keywords: Big-data ، Energy efficiency assessment ، K-means ، Multi-dimension association rules |
مقاله انگلیسی |