Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Machine learning for property price prediction and price valuation: a systematic literature review
NS Ja'afar, J Mohamad, S Ismail - Planning Malaysia, 2021 - planningmalaysia.org
Abstract Machine learning is a branch of artificial intelligence that allows software
applications to be more accurate in its data predicting, as well as to predict current …
applications to be more accurate in its data predicting, as well as to predict current …
Predicting bitcoin price movements using sentiment analysis: a machine learning approach
Purpose Cryptocurrencies such as Bitcoin (BTC) attracted a lot of attention in recent months
due to their unprecedented price fluctuations. This paper aims to propose a new method for …
due to their unprecedented price fluctuations. This paper aims to propose a new method for …
Forecasting COVID-19: vector autoregression-based model
Forecasting the spread of COVID-19 infection is an important aspect of public health
management. In this paper, we propose an approach to forecasting the spread of the …
management. In this paper, we propose an approach to forecasting the spread of the …
Comparative analysis of activation functions in neural networks
Although the impact of activations on the accuracy of neural networks has been covered in
the literature, there is little discussion about the relationship between the activations and the …
the literature, there is little discussion about the relationship between the activations and the …
Unlocking ETF price forecasting: Exploring the interconnections with statistical dependence-based graphs and xAI techniques
In the complex landscape of financial markets, accurately predicting Exchange-Traded Fund
(ETF) price movements requires advanced methodologies. This research introduces a …
(ETF) price movements requires advanced methodologies. This research introduces a …
Comparative analysis of machine learning models in predicting housing prices: a case study of Prishtina's real estate market
V Hoxha - International Journal of Housing Markets and Analysis, 2024 - emerald.com
Purpose The purpose of this study is to carry out a comparative analysis of four machine
learning models such as linear regression, decision trees, k-nearest neighbors and support …
learning models such as linear regression, decision trees, k-nearest neighbors and support …
Energy crypto currencies and leading US energy stock prices: are Fibonacci retracements profitable?
This paper investigates the role of Fibonacci retracements levels, a popular technical
analysis indicator, in predicting stock prices of leading US energy companies and energy …
analysis indicator, in predicting stock prices of leading US energy companies and energy …
Bitcoin price forecasting: Linear discriminant analysis with sentiment evaluation
Cryptocurrencies such as bitcoin have garnered a lot of attention in recent months due to
their meteoric rise. In this paper, we propose a new method for predicting the direction of …
their meteoric rise. In this paper, we propose a new method for predicting the direction of …
Early COVID-19 policy response on healthcare equity prices
I Gurrib - Studies in Economics and Finance, 2021 - emerald.com
Purpose This paper aims to investigate the implementation of the short selling ban policy
imposed by the Italian stock exchange on health-care stock prices, as a tool to mitigate …
imposed by the Italian stock exchange on health-care stock prices, as a tool to mitigate …