Results 161 to 170 of about 20,682 (248)
Cryptocurrency interest in geographical regions with high unemployment rates
Elif BEZİRGAN
openalex +1 more source
ABSTRACT Time and chronology form the invisible architecture upon which modern civilization depends, governing synchronization across markets, power grids, communication networks, transportation, and defense. Yet, this shared temporal framework, engineered through atomic clocks, satellites, and digital synchronization, faces growing vulnerabilities ...
Bilal M. Ayyub
wiley +1 more source
An empirical evaluation of fuzzy bidirectional long short-term memory with soft computing based decision-making model for predicting volatility of cryptocurrencies. [PDF]
Ragab M.
europepmc +1 more source
Comparison of Linear Regression and LSTM (Long Short-Term Memory) in Cryptocurrency Prediction
Marisa Istaltofa +2 more
openalex +2 more sources
Measuring Consumer Alienation in the Digital Market: Scale Development and Validation
ABSTRACT This study re‐evaluates the concept of consumer alienation in the context of the digital marketplace. With the transformation brought about by the Fourth Industrial Revolution, traditional views on consumer alienation, which emphasize a psychological state of market isolation, require updating.
Yu Lim Lee, Jae‐Eun Chung
wiley +1 more source
A swarm-optimization based fusion model of sentiment analysis for cryptocurrency price prediction. [PDF]
Tiwari D +5 more
europepmc +1 more source
The Influence of Cryptocurrency Transaction as a Currency in NFT-Based Game Transactions
Kian Win Hartono, Tanty Oktavia
openalex +1 more source
The results of this paper show that incorporating ML predictions with a confidence ratio significantly improves profitability, achieving a 258.5% profit and ~60% increase in total balance compared with traditional non‐ML strategies. By leveraging ML algorithms like multilayer perceptron, this approach enhances decision‐making and outperforms competing ...
Kristína Okasová +2 more
wiley +1 more source
Evaluating machine learning models for predictive accuracy in cryptocurrency price forecasting. [PDF]
Qureshi SM +6 more
europepmc +1 more source

