A review of sentiment, semantic and event-extraction-based approaches in stock forecasting
Stock forecasting is a significant and challenging task. The recent development of web
technologies has transformed the communication channel to allow the public to share …
technologies has transformed the communication channel to allow the public to share …
Algorithmic trading and short-term forecast for financial time series with machine learning models; state of the art and perspectives
Stock price prediction with machine learning is an oft-studied area where numerous
unsolved problems still abound owing to the high complexity and volatility that technical …
unsolved problems still abound owing to the high complexity and volatility that technical …
Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning
Pollution control and environmental protection of the Yangtze River have received major
attention in China. However, modeling the river's pollution load remains challenging due to …
attention in China. However, modeling the river's pollution load remains challenging due to …
Comparison of machine learning techniques for condition assessment of sewer network
L Van Nguyen, DT Bui, R Seidu - IEEE Access, 2022 - ieeexplore.ieee.org
Assessment of sewer condition is one of the critical steps in asset management and support
investment decisions; therefore, condition assessment models with high accuracy are …
investment decisions; therefore, condition assessment models with high accuracy are …
The bitcoin halving cycle volatility dynamics and safe haven-hedge properties: A MSGARCH approach
This paper introduces a unique perspective towards Bitcoin safe haven and hedge
properties through the Bitcoin halving cycle. The Bitcoin halving cycle suggests that Bitcoin …
properties through the Bitcoin halving cycle. The Bitcoin halving cycle suggests that Bitcoin …
Intrusion Detection Schemes Based on Synthetic Minority Oversampling Technique and Machine Learning Models
With the progression and sophistication of technology, the frequency and intricacy of cyber-
attacks also escalate. Malicious hackers and cybercriminals are perpetually devising novel …
attacks also escalate. Malicious hackers and cybercriminals are perpetually devising novel …
[PDF][PDF] The Bitcoin Halving Cycle Volatility Dynamics and Safe Haven-Hedge Properties: A MSGARCH Approach
This paper introduces a unique perspective towards Bitcoin safe haven and hedge
properties through the Bitcoin halving cycle. The Bitcoin halving cycle suggests that Bitcoin …
properties through the Bitcoin halving cycle. The Bitcoin halving cycle suggests that Bitcoin …
Support resistance levels towards profitability in intelligent algorithmic trading models
Past studies showed that more advanced model architectures and techniques are being
developed for intelligent algorithm trading, but the input features of the models across these …
developed for intelligent algorithm trading, but the input features of the models across these …
A correlation-embedded attention approach to mitigate multicollinearity in foreign exchange data using LSTM
MHS Leow - 2023 - eprints.utar.edu.my
Technologies currently drive the collection of big data in various fields, including algorithmic
trading. This leads to a notable increase in the collection and storage of variables and data …
trading. This leads to a notable increase in the collection and storage of variables and data …
Comparison of Machine Learning Techniques for Structural Condition Assessment of Sewer Network
L Nguyen Van, D Tien Bui, R Seidu - 2022 - ntnuopen.ntnu.no
Assessment of sewer condition is one of the critical steps in asset management and support
investment decisions; therefore, condition assessment models with high accuracy are …
investment decisions; therefore, condition assessment models with high accuracy are …