Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the …
The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …
autonomous software that optimizes decision-making and energy distribution operations …
A comprehensive survey on recent metaheuristics for feature selection
Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …
preprocessing due to the ever-increasing sizes in actual data. There have been many …
A topic modeling comparison between lda, nmf, top2vec, and bertopic to demystify twitter posts
The richness of social media data has opened a new avenue for social science research to
gain insights into human behaviors and experiences. In particular, emerging data-driven …
gain insights into human behaviors and experiences. In particular, emerging data-driven …
[HTML][HTML] Review of image classification algorithms based on convolutional neural networks
L Chen, S Li, Q Bai, J Yang, S Jiang, Y Miao - Remote Sensing, 2021 - mdpi.com
Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …
emergence of deep learning has promoted the development of this field. Convolutional …
Digital twin: Values, challenges and enablers from a modeling perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
Big data analytics in building the competitive intelligence of organizations
J Ranjan, C Foropon - International Journal of Information Management, 2021 - Elsevier
Over recent years, organizations have started to capitalize on the significant use of Big Data
and emerging technologies to analyze, and gain valuable insights linked to, decision …
and emerging technologies to analyze, and gain valuable insights linked to, decision …
Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …
giving directions of solar energy conversion systems (design, modeling, and operation) …
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
The state of the art in deep learning applications, challenges, and future prospects: A comprehensive review of flood forecasting and management
Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …
people. Accurate flood forecasts and control are essential to lessen these effects and …
Literature review of Industry 4.0 and related technologies
Manufacturing industry profoundly impact economic and societal progress. As being a
commonly accepted term for research centers and universities, the Industry 4.0 initiative has …
commonly accepted term for research centers and universities, the Industry 4.0 initiative has …