NILM techniques for intelligent home energy management and ambient assisted living: A review
The ongoing deployment of smart meters and different commercial devices has made
electricity disaggregation feasible in buildings and households, based on a single measure …
electricity disaggregation feasible in buildings and households, based on a single measure …
Industry 4.0 and demand forecasting of the energy supply chain: A literature review
The number of publications in demand forecasting of the energy supply chain augmented
meaningfully due to the 2008 global financial crisis and its consequence on the global …
meaningfully due to the 2008 global financial crisis and its consequence on the global …
DB-Net: A novel dilated CNN based multi-step forecasting model for power consumption in integrated local energy systems
In the era of cutting edge technology, excessive demand for electricity is rising day by day,
due to the exponential growth of population, electricity reliant vehicles, and home …
due to the exponential growth of population, electricity reliant vehicles, and home …
Short-term prediction of residential power energy consumption via CNN and multi-layer bi-directional LSTM networks
Excessive Power Consumption (PC) and demand for power is increasing on a daily basis,
due to advancements in technology, the rise in electricity-dependent machinery, and the …
due to advancements in technology, the rise in electricity-dependent machinery, and the …
Energy consumption forecasting based on Elman neural networks with evolutive optimization
Buildings are an essential part of our social life. People spend a substantial fraction of their
time and spend a high amount of energy in them. There is a grand variety of systems and …
time and spend a high amount of energy in them. There is a grand variety of systems and …
Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction
Z Liu, D Wu, Y Liu, Z Han, L Lun… - Energy Exploration …, 2019 - journals.sagepub.com
It is of great significance to achieve the prediction of building energy consumption. However,
machine learning, as a promising technique for many practical applications, was rarely …
machine learning, as a promising technique for many practical applications, was rarely …
A prediction methodology of energy consumption based on deep extreme learning machine and comparative analysis in residential buildings
M Fayaz, DH Kim - Electronics, 2018 - mdpi.com
In this paper, we have proposed a methodology for energy consumption prediction in
residential buildings. The proposed method consists of four different layers, namely data …
residential buildings. The proposed method consists of four different layers, namely data …
Large-scale integration of renewable energies by 2050 through demand prediction with ANFIS, Ecuador case study
The growing reliance on hydroelectric power and the risk of future droughts pose significant
challenges for power systems, especially in develo** countries. To address these …
challenges for power systems, especially in develo** countries. To address these …
Planning of electrical energy for the Galapagos Islands using different renewable energy technologies
The present study focuses on the planning of electrical energy for the Galapagos islands
using different renewable energy technologies for the year 2031 in order to reduce diesel …
using different renewable energy technologies for the year 2031 in order to reduce diesel …
Deep learning techniques for energy forecasting and condition monitoring in the manufacturing sector
VJ Mawson, BR Hughes - Energy and Buildings, 2020 - Elsevier
The industrial and building sector demands the largest proportion of global energy, therefore
adopting energy efficiency related strategies, optimization techniques and management is …
adopting energy efficiency related strategies, optimization techniques and management is …