A review of distributed acoustic sensing applications for railroad condition monitoring
Accurate condition monitoring has been a major challenge among railroad management
authorities as they work to minimize collisions that lead to fatalities or damage to railroads …
authorities as they work to minimize collisions that lead to fatalities or damage to railroads …
DL-GuesS: Deep Learning and Sentiment Analysis-Based Cryptocurrency Price Prediction
Cryptocurrencies are peer-to-peer-based transaction systems where the data exchanges
are secured using the secure hash algorithm (SHA)-256 and message digest (MD)-5 …
are secured using the secure hash algorithm (SHA)-256 and message digest (MD)-5 …
Fusion in cryptocurrency price prediction: A decade survey on recent advancements, architecture, and potential future directions
Cryptographic forms of money are distributed peer-to-peer (P2P) computerized exchange
mediums, where the exchanges or records are secured through a protected hash set of …
mediums, where the exchanges or records are secured through a protected hash set of …
Predicting macro-financial instability–How relevant is sentiment? Evidence from long short-term memory networks
This paper examines the relevance of sentiment in predicting overall financial system
instability using long-run short-term memory networks. Weekly data on the US financial …
instability using long-run short-term memory networks. Weekly data on the US financial …
Encoder–Decoder Based LSTM and GRU Architectures for Stocks and Cryptocurrency Prediction
This work addresses the intricate task of predicting the prices of diverse financial assets,
including stocks, indices, and cryptocurrencies, each exhibiting distinct characteristics and …
including stocks, indices, and cryptocurrencies, each exhibiting distinct characteristics and …
Split-Second Cryptocurrency Forecast Using Prognostic Deep Learning Algorithms: Data Curation by Deephaven
Cryptocurrency is a popular digital currency due to its security and peer-to-peer
transferability. Predicting cryptocurrency prices is crucial for investors and traders to make …
transferability. Predicting cryptocurrency prices is crucial for investors and traders to make …
The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Review
T Liu, Y Wang, J Sun, Y Tian, Y Huang, T Xue… - arXiv preprint arXiv …, 2024 - arxiv.org
As blockchain technology rapidly evolves, the demand for enhanced efficiency, security, and
scalability grows. Transformer models, as powerful deep learning architectures, have shown …
scalability grows. Transformer models, as powerful deep learning architectures, have shown …
[HTML][HTML] Predicting small molecules solubility on endpoint devices using deep ensemble neural networks
Aqueous solubility is a valuable yet challenging property to predict. Computing solubility
using first-principles methods requires accounting for the competing effects of entropy and …
using first-principles methods requires accounting for the competing effects of entropy and …
A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity
V Shkurastky, AB Usman, M O'Dea… - … of Computer and …, 2024 - sure.sunderland.ac.uk
—This paper examines relationships between solar activity and earthquakes, it applied
machine learning techniques: Knearest neighbour, support vector regression, random forest …
machine learning techniques: Knearest neighbour, support vector regression, random forest …
Encoder–Decoder Based LSTM and GRU Architectures for Stocks and Cryptocurrency Prediction
This work addresses the intricate task of predicting the prices of diverse financial assets,
including stocks, indices, and cryptocurrencies, each exhibiting distinct characteristics and …
including stocks, indices, and cryptocurrencies, each exhibiting distinct characteristics and …