Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for CPS
Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …
[HTML][HTML] A systematic review of machine learning techniques related to local energy communities
In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …
processes in several sectors, as in the case of electrical power systems. Machine learning …
Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future
The rapid development and implementation of smart and IoT (Internet of Things) based
technologies have allowed for various possibilities in technological advancements for …
technologies have allowed for various possibilities in technological advancements for …
Machine learning based energy management model for smart grid and renewable energy districts
The combination of renewable energy sources and prosumer-based smart grid is a
sustainable solution to cater to the problem of energy demand management. A pressing …
sustainable solution to cater to the problem of energy demand management. A pressing …
Regression modeling for enterprise electricity consumption: A comparison of recurrent neural network and its variants
Effective electricity consumption forecasting is extremely significant for enterprises' electricity
planning which can provide data support for production decision, thus improving the level of …
planning which can provide data support for production decision, thus improving the level of …
Machine learning based demand response scheme for IoT enabled PV integrated smart building
P Balakumar, T Vinopraba… - Sustainable Cities and …, 2023 - Elsevier
The short-term forecasting of electric power consumption and renewable energy generation
with high efficiency and advanced demand side management is essential for improving the …
with high efficiency and advanced demand side management is essential for improving the …
A hybrid short-term load forecasting approach for individual residential customer
This article proposes a hybrid method (HM) to improve the accuracy of short-term individual
residential load forecasting. The HM includes an ensemble model (EM), deep ensemble …
residential load forecasting. The HM includes an ensemble model (EM), deep ensemble …
Power consumption forecast model using ensemble learning for smart grid
The prediction of power consumption of smart meters plays a vital role in power distribution
and management in the smart grid, which depends on real-time and historical data …
and management in the smart grid, which depends on real-time and historical data …
Research on central air conditioning systems and an intelligent prediction model of building energy load
L Pan, S Wang, J Wang, M Xiao, Z Tan - Energies, 2022 - mdpi.com
The central air conditioning system provides city dwellers with an efficient and comfortable
environment. Meanwhile, coinciding with their use, the building electricity load is increased …
environment. Meanwhile, coinciding with their use, the building electricity load is increased …
Prediction of domestic power peak demand and consumption using supervised machine learning with smart meter dataset
R Geetha, K Ramyadevi… - Multimedia Tools and …, 2021 - Springer
The prediction of electricity consumption is a vital foundation for smart energy management.
Since the consumption of power varies with different appliances, better forecasting of power …
Since the consumption of power varies with different appliances, better forecasting of power …