...Mohammad Vahidpour; Amir Daneshvar; Mohsen Amini Khouzani; Mahdi Homayounfar Purpose This study aims to enhance cryptocurrency price and trend prediction by applying advanced machine learning (ML) techniques. Given the market’s high volatility and complexity, the research identifies effective...

...Orhan Ali Nooruldeen; Shahram Azizifar; Ahmed Ghareeb; Ali Hussein Abdulkarim; Mohamed M. Awad Purpose To develop a hybrid machine-learning framework that integrates a Physics-Informed Neural Network (PINN) with Particle Swarm Optimization (PSO)–tuned regression models to deliver fast, accurate...

...Vimala Balakrishnan; Aainaa Nadia Mohammed Hashim; Voon Chung Lee; Voon Hee Lee; Ying Qiu Lee Purpose This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019. Design/methodology/approach Exploratory data...

... at the network edge. 20 12 2022 19 01 2023 31 01 2023 03 02 2023 © Emerald Publishing Limited 2023 Emerald Publishing Limited Licensed re-use rights only SDN Campus network Deep learning Artificial intelligence Machine learning In recent years, there has been...

... of the rise and fall of the stock outperform than the model with LSTM only as well as other machine learning models. Furthermore, the efficiency of parameter adjustment is greatly higher than other hyperparameter optimization methods. Originality/value (1) The AGA-LSTM algorithm is used to input various...

... on fake news detection approaches on deep learning and machine learning. The papers were initially searched through the Google scholar platform, and they have been scrutinized for quality. The authors kept “Scopus” and “Web of Science” as quality indexing parameters. All research gaps and available...

... that were financial disappointments. Using temporal tweet patterns, a number of machine learning models were developed and their predictive performance was compared. Findings Results show that the temporal patterns of tweet volume, length and sentiment differ between “hits” and “busts” in the days...

... and precision compared to existing algorithms. Design/methodology/approach A simulation setup of the aerial vehicle guidance problem is developed. A model-based machine learning technique known as Q-learning is used to develop a new guidance scheme. Several simulation experiments are conducted to train...