Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms
In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …
[HTML][HTML] Supply chain risk management with machine learning technology: A literature review and future research directions
Abstract Coronavirus disease 2019 (COVID-19) has placed tremendous pressure on supply
chain risk management (SCRM) worldwide. Recent technological advances, especially …
chain risk management (SCRM) worldwide. Recent technological advances, especially …
Intelligent video anomaly detection and classification using faster RCNN with deep reinforcement learning model
RF Mansour, J Escorcia-Gutierrez, M Gamarra… - Image and Vision …, 2021 - Elsevier
Recently, intelligent video surveillance applications have become essential in public
security by the use of computer vision technologies to investigate and understand long video …
security by the use of computer vision technologies to investigate and understand long video …
Hybridization of hybrid structures for time series forecasting: A review
Z Hajirahimi, M Khashei - Artificial Intelligence Review, 2023 - Springer
Achieving the desired accuracy in time series forecasting has become a binding domain,
and developing a forecasting framework with a high degree of accuracy is one of the most …
and developing a forecasting framework with a high degree of accuracy is one of the most …
Artificial intelligence based quality of transmission predictive model for cognitive optical networks
Due to the advancements in 5 G technologies, high-definition, and the internet of things
(IoT), the capacity demand of optical networks has been exponentially increased. Optical …
(IoT), the capacity demand of optical networks has been exponentially increased. Optical …
Deep learning-based model for financial distress prediction
Predicting bankruptcies and assessing credit risk are two of the most pressing issues in
finance. Therefore, financial distress prediction and credit scoring remain hot research topics …
finance. Therefore, financial distress prediction and credit scoring remain hot research topics …
An Efficient Outlier Detection with Deep Learning‐Based Financial Crisis Prediction Model in Big Data Environment
Y Venkateswarlu, K Baskar, A Wongchai… - Computational …, 2022 - Wiley Online Library
As Big Data, Internet of Things (IoT), cloud computing (CC), and other ideas and
technologies are combined for social interactions. Big data technologies improve the …
technologies are combined for social interactions. Big data technologies improve the …
Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms
In the digital era, innovations in business intelligence are critical to staying competitive and
popular across the growing business trends. Businesses have begun to investigate the next …
popular across the growing business trends. Businesses have begun to investigate the next …
Failure prediction of Indian Banks using SMOTE, Lasso regression, bagging and boosting
Banks have a vital role in the financial system and its survival is crucial for the stability of the
economy. This research paper attempts to create an efficient and appropriate predictive …
economy. This research paper attempts to create an efficient and appropriate predictive …
The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions
Abstract Since December 2019, the COVID-19 outbreak has resulted in countless deaths
and has harmed all facets of human existence. COVID-19 has been designated an epidemic …
and has harmed all facets of human existence. COVID-19 has been designated an epidemic …