A comprehensive study of artificial intelligence and cybersecurity on bitcoin, crypto currency and banking system

T Choithani, A Chowdhury, S Patel, P Patel… - Annals of Data …, 2024 - Springer
In recent years cryptocurrencies are emerging as a prime digital currency as an important
asset and financial system is also emerging as an important aspect. To reduce the risk of …

[HTML][HTML] An outliers detection and elimination framework in classification task of data mining

CSK Dash, AK Behera, S Dehuri, A Ghosh - Decision Analytics Journal, 2023 - Elsevier
An outlier is a datum that is far from other data points in which it occurs. It can have a
considerable impact on the output. Therefore, removing or resolving it before the analysis is …

A CNN-LSTM-based hybrid deep learning approach for sentiment analysis on Monkeypox tweets

KK Mohbey, G Meena, S Kumar, K Lokesh - New Generation Computing, 2024 - Springer
The research on sentiment analysis has shown a great deal of utility in the field of public
health, specifically in the investigation of infectious illnesses. As the world begins to …

[HTML][HTML] A hybrid deep learning approach for detecting sentiment polarities and knowledge graph representation on monkeypox tweets

G Meena, KK Mohbey, S Kumar, K Lokesh - Decision Analytics Journal, 2023 - Elsevier
People have recently begun communicating their thoughts and viewpoints through user-
generated multimedia material on social networking websites. This information can be …

Identifying Bulls and bears? A bibliometric review of applying artificial intelligence innovations for stock market prediction

R Chopra, GD Sharma, V Pereira - Technovation, 2024 - Elsevier
The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI)
has become overwhelming, making it quite challenging for academics and relevant …

Variational Autoencoders‐BasedSelf‐Learning Model for Tumor Identification and Impact Analysis from 2‐D MRI Images

P Naga Srinivasu, TB Krishna, S Ahmed… - Journal of …, 2023 - Wiley Online Library
Over the past few years, a tremendous change has occurred in computer‐aided diagnosis
(CAD) technology. The evolution of numerous medical imaging techniques has enhanced …

[HTML][HTML] Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network

Z Mustaffa, MH Sulaiman - International Journal of Cognitive Computing in …, 2023 - Elsevier
Abstract Artificial Neural Network (ANN) is an effective machine learning technique for
addressing regression tasks. Nonetheless, the performance of ANN is highly dependent on …

[HTML][HTML] An exploratory data analysis approach for analyzing financial accounting data using machine learning

P Chakri, S Pratap, SK Gouda - Decision Analytics Journal, 2023 - Elsevier
Analyzing financial accounting transactions is essential for gaining valuable hidden insights,
optimizing performance, reducing expenses by identifying more efficient methods of …

SMP-DL: a novel stock market prediction approach based on deep learning for effective trend forecasting

WM Shaban, E Ashraf, AE Slama - Neural Computing and Applications, 2024 - Springer
As the economy has grown rapidly in recent years, more and more people have begun
putting their money into the stock market. Thus, predicting trends in the stock market is …

Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately

A Lawi, H Mesra, S Amir - Journal of Big Data, 2022 - Springer
Stocks are an attractive investment option because they can generate large profits
compared to other businesses. The movement of stock price patterns in the capital market is …