能源领域的大数据分析和预测建模方法

Roberto Corizzo, Michelangelo Ceci, D. Malerba
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引用次数: 3

摘要

本文描述了在能源部门背景下产生的地理分布式传感器数据分析中取得的最新成果。所描述的方法植根于大数据分析和预测建模研究领域,并且基于分布式架构。他们通过考虑数据异常的检测和处理,来解决能源生产工厂网络的能源预测任务。这项研究是由欧洲委员会和许多国家政府资助的研究项目的目标所推动和一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector
This paper describes recent results achieved in the analysis of geo-distributed sensor data generated in the context of the energy sector. The approaches described have roots in the Big Data Analytics and Predictive Modeling research fields and are based on distributed architectures. They tackle the energy forecasting task for a network of energy production plants, by also taking into consideration the detection and treatment of anomalies in the data. This research is motivated by and consistent with the objectives of research projects funded by the European Commission and by many national governments.
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