Energy consumption in buildings has steadily increased. Buildings consume more energy
than necessary due to suboptimal design and operation. Apart from retro-fitting, not much …

Purpose This paper aims to focus on data analytic tools and integrated data analyzing
approaches used on smart energy meters (SEMs). Furthermore, while observing the diverse …

Based on improved complete ensemble empirical mode decomposition with adaptive noise
(ICEEMDAN) algorithm and kernel online sequential extreme learning machine (KOSELM) …

In this paper, we present early results on the use of deep reinforcement learning (DRL) for
maximizing anomaly detection performance in buildings. We conjecture that DRL can …

In demand response (DR) based on contracts with consumers, some participants have the
potential to default on providing their scheduled negawatt energy due to demand-side …

In current energy production and distribution system, a smart energy meter has been a
significant conceptual paradigm. There is a dire requirement to make energy usage more …

Detecting and removing anomalies in the time series describing physical phenomena is a
big challenge faced by scientists from many fields. The aim of the article is to present the …

Authentication and authorization systems can be found in almost every software system, and
consequently affects every aspect of our lives. Despite the variety in the software that relies …

摘要异常能耗预警是工业过程节能的重要内容. 然而, 对于通常能耗巨大的铅冶炼行业的相关
研究却鲜有报道. 因此, 本研究建立了基于智能能耗预测和异常能耗识别的预警系统 …

The rapidly growing demand for energy poses one of the biggest challenges in our society.
This challenge is critical not just for the power utilities but also for the environment as it leads …