Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives
Y Hu, Y Man - Renewable and Sustainable Energy Reviews, 2023 - Elsevier
The industrial process consumes substantial energy and emits large amounts of carbon
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …
Key technologies for smart energy systems: Recent developments, challenges, and research opportunities in the context of carbon neutrality
Energy crisis and environmental pollution have expedited the transition of the energy
system. Global use of low-carbon energy has increased from 1: 6.16 to 1: 5.37. Smart energy …
system. Global use of low-carbon energy has increased from 1: 6.16 to 1: 5.37. Smart energy …
Boosted ANFIS model using augmented marine predator algorithm with mutation operators for wind power forecasting
There are several major available renewable energies, such as wind power which can be
considered one of the most potential energy resources. Thus, wind power is a vital green …
considered one of the most potential energy resources. Thus, wind power is a vital green …
Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model
D Niu, L Sun, M Yu, K Wang - Energy, 2022 - Elsevier
Accurate and reliable wind power forecasting (WPF) is significant for ensuring power
systems' economic operation and safe dispatching and for reducing the technical and …
systems' economic operation and safe dispatching and for reducing the technical and …
Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment
S Jafarzadeh Ghoushchi… - Neural computing and …, 2023 - Springer
There are a lot of elements that make road safety assessment situations unpredictable and
hard to understand. This could put people's lives in danger, hurt the mental health of a …
hard to understand. This could put people's lives in danger, hurt the mental health of a …
A data-driven deep sequence-to-sequence long-short memory method along with a gated recurrent neural network for wind power forecasting
Large amounts of wind power generation have an impact not only on energy markets but
also on wholesale and retail market designs. Simultaneously, technological issues arise as …
also on wholesale and retail market designs. Simultaneously, technological issues arise as …
A novel seasonal adaptive grey model with the data-restacking technique for monthly renewable energy consumption forecasting
S Ding, Z Tao, R Li, X Qin - Expert Systems with Applications, 2022 - Elsevier
To provide accurate renewable energy forecasts that adapt to the country's sustainable
development, a novel seasonal model combined with the data-restacking technique is …
development, a novel seasonal model combined with the data-restacking technique is …
FWNNet: Presentation of a New Classifier of Brain Tumor Diagnosis Based on Fuzzy Logic and the Wavelet‐Based Neural Network Using Machine‐Learning Methods
M Ahmadi, F Dashti Ahangar, N Astaraki… - Computational …, 2021 - Wiley Online Library
In this paper, we present a novel classifier based on fuzzy logic and wavelet transformation
in the form of a neural network. This classifier includes a layer to predict the numerical …
in the form of a neural network. This classifier includes a layer to predict the numerical …
Leveraging heat accumulation of district heating network to improve performances of integrated energy system under source-load uncertainties
J Wang, S Huo, R Yan, Z Cui - Energy, 2022 - Elsevier
The multiple uncertainties in renewable energy and loads and the thermoelectric coupling
characteristic of the integrated energy system (IES) restrict the accommodation of renewable …
characteristic of the integrated energy system (IES) restrict the accommodation of renewable …
Coordinated control of wind turbine and hybrid energy storage system based on multi-agent deep reinforcement learning for wind power smoothing
X Wang, J Zhou, B Qin, L Guo - Journal of Energy Storage, 2023 - Elsevier
Due to the inherent fluctuation, wind power integration into the large-scale grid brings
instability and other safety risks. In this study by using a multi-agent deep reinforcement …
instability and other safety risks. In this study by using a multi-agent deep reinforcement …