A comprehensive review on food waste reduction based on IoT and big data technologies
Food waste reduction, as a major application area of the Internet of Things (IoT) and big data
technologies, has become one of the most pressing issues. In recent years, there has been …
technologies, has become one of the most pressing issues. In recent years, there has been …
[HTML][HTML] A systematic review of machine learning applications in the operation of smart distribution systems
Due to climate changes happening in the past few years, the necessity for the integration of
renewable energy sources and other low-carbon technologies is ever-growing. With the …
renewable energy sources and other low-carbon technologies is ever-growing. With the …
Impact of the COVID-19 pandemic on electricity demand and load forecasting
The current COVID-19 pandemic and the preventive measures taken to contain the spread
of the disease have drastically changed the patterns of our behavior. The pandemic and …
of the disease have drastically changed the patterns of our behavior. The pandemic and …
Functional Data Approach for Short‐Term Electricity Demand Forecasting
In today's liberalized electricity markets, modeling and forecasting electricity demand data
are highly important for the effective management of the power system. However, electricity …
are highly important for the effective management of the power system. However, electricity …
Fuzzy logic-model predictive control energy management strategy for a dual-mode locomotive
Fuel cell hybrid electric vehicles (FC–HEV) combine the high energy density of hydrogen
with a high-power density energy storage system. This favors the response to sudden …
with a high-power density energy storage system. This favors the response to sudden …
Photovoltaic power forecasting using wavelet neuro-fuzzy for active solar trackers
SF Stefenon, C Kasburg, RZ Freire… - Journal of Intelligent …, 2021 - content.iospress.com
The generation of electric energy by photovoltaic (PV) panels depends on many parameters,
one of them is the sun's angle of incidence. By using solar active trackers, it is possible to …
one of them is the sun's angle of incidence. By using solar active trackers, it is possible to …
Stacking ensemble methodology using deep learning and ARIMA models for short-term load forecasting
PMR Bento, JAN Pombo, MRA Calado, SJPS Mariano - Energies, 2021 - mdpi.com
Short-Term Load Forecasting is critical for reliable power system operation, and the search
for enhanced methodologies has been a constant field of investigation, particularly in an …
for enhanced methodologies has been a constant field of investigation, particularly in an …
Analysis of the impact of clustering techniques and parameters on evolutionary-based hybrid models for forecasting electricity consumption
Electricity is undeniably one of the most crucial building blocks of high-quality life all over the
world. Like many other African countries, Nigeria is still grappling with the challenge of the …
world. Like many other African countries, Nigeria is still grappling with the challenge of the …
Application of optimized GM (1, 1) model based on EMD in landslide deformation prediction
C Huang, Y Cao, L Zhou - Computational and Applied Mathematics, 2021 - Springer
The monitoring data of landslide deformation are characterized by non-smooth, nonlinear
and random changes, and the cumulative changes of the monitored objects have both …
and random changes, and the cumulative changes of the monitored objects have both …
Time series forecasting for decision making on city-wide energy demand: a comparative study
Time series modeling and forecasting are critical in various practical applications, including
the energy sector, and have been actively investigated in this field for several years. Many …
the energy sector, and have been actively investigated in this field for several years. Many …