AB-net: A novel deep learning assisted framework for renewable energy generation forecasting
Renewable energy (RE) power plants are deployed globally because the renewable energy
sources (RESs) are sustainable, clean, and environmentally friendly. However, the demand …
sources (RESs) are sustainable, clean, and environmentally friendly. However, the demand …
Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression
DB Vukovic, K Romanyuk, S Ivashchenko… - Expert systems with …, 2022 - Elsevier
This paper investigates the forecasting performance for credit default swap (CDS) spreads
by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short …
by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short …
Inferring storefront vacancy using mobile sensing images and computer vision approaches
Storefront vacancy has been a widespread and worldwide phenomenon, raising concerns
about the changing characteristic of the retail landscape, loss of community vitality, and …
about the changing characteristic of the retail landscape, loss of community vitality, and …
A Novel Improved Variational Mode Decomposition-Temporal Convolutional Network-Gated Recurrent Unit with Multi-Head Attention Mechanism for Enhanced …
H Fu, J Zhang, S Xie - Electronics, 2024 - mdpi.com
Photovoltaic (PV) power forecasting plays a crucial role in optimizing renewable energy
integration into the grid, necessitating accurate predictions to mitigate the inherent variability …
integration into the grid, necessitating accurate predictions to mitigate the inherent variability …
Exploiting script similarities to compensate for the large amount of data in training tesseract lstm: Towards kurdish ocr
Featured Application This work helps in the preparation of OCR for the Kurdish language. In
particular, its focus is on Kurdish texts written in Persian-Arabic script. Currently, Kurdish …
particular, its focus is on Kurdish texts written in Persian-Arabic script. Currently, Kurdish …
Deep Learning for Predicting Perceived Decline Scores in Built Environments: A Case Study of S. Korea
M Kim, Y Park, J Lee, HW Kim, J Kim - Korea - papers.ssrn.com
The decline of Seoul's commercial district is intensifying due to competition among the self-
employed, the impact of COVID-19, and reduced physical shopping. The initial step in …
employed, the impact of COVID-19, and reduced physical shopping. The initial step in …
A Novel Hierarchical Lstm for Photovoltaic Power Forecasting Strategy
J Zhang, H Fu, S Xie - Available at SSRN 4561975 - papers.ssrn.com
The uncertainty of photovoltaic power generation may affect the balance between power
demand and production, bringing severe challenges to the photovoltaic power grid system …
demand and production, bringing severe challenges to the photovoltaic power grid system …
[PDF][PDF] Net: A Novel Deep Learning Assisted Framework for Renewable Energy Generation Forecasting. Mathematics 2021, 9, 2456
Renewable energy (RE) power plants are deployed globally because the renewable energy
sources (RESs) are sustainable, clean, and environmentally friendly. However, the demand …
sources (RESs) are sustainable, clean, and environmentally friendly. However, the demand …