Financial applications of machine learning: A literature review
N Nazareth, YVR Reddy - Expert Systems with Applications, 2023 - Elsevier
This systematic literature review analyses the recent advances of machine learning and
deep learning in finance. The study considers six financial domains: stock markets, portfolio …
deep learning in finance. The study considers six financial domains: stock markets, portfolio …
Conceptual structure and perspectives on “innovation management”: A bibliometric review
The present study aims to analyze “Innovation Management” using a bibliometric technique.
To this aim, Web of Science (WOS) citation database was used to extract the articles. Then …
To this aim, Web of Science (WOS) citation database was used to extract the articles. Then …
[HTML][HTML] Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions
Artificial intelligence (AI) is a set of rapidly expanding disruptive technologies that are
radically transforming various aspects related to people, business, society, and the …
radically transforming various aspects related to people, business, society, and the …
[HTML][HTML] Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach
Portfolio optimization concerns with periodically allocating the limited funds to invest in a
variety of potential assets in order to satisfy investors' appetites for risk and return goals …
variety of potential assets in order to satisfy investors' appetites for risk and return goals …
COVID-19 vaccine hesitancy: a social media analysis using deep learning
Hesitant attitudes have been a significant issue since the development of the first vaccines—
the WHO sees them as one of the most critical global health threats. The increasing use of …
the WHO sees them as one of the most critical global health threats. The increasing use of …
The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods
In recent years, machine learning models based on big data have been introduced into
marketing in order to transform customer data into meaningful insights and to make strategic …
marketing in order to transform customer data into meaningful insights and to make strategic …
Can customer sentiment impact firm value? An integrated text mining approach
P Eachempati, PR Srivastava, A Kumar… - … Forecasting and Social …, 2022 - Elsevier
Developing measures to capture customer sentiment and securing a positive customer
experience is a strategic necessity to improve firm profitability and shareholder value. The …
experience is a strategic necessity to improve firm profitability and shareholder value. The …
District heating load prediction algorithm based on bidirectional long short-term memory network model
M Cui - Energy, 2022 - Elsevier
Heating load prediction based on machine learning algorithms has received increasing
attention, especially the Long Short Term Memory (LSTM) network, have been shown to …
attention, especially the Long Short Term Memory (LSTM) network, have been shown to …
Incorporating causality in energy consumption forecasting using deep neural networks
K Sharma, YK Dwivedi, B Metri - Annals of Operations Research, 2024 - Springer
Forecasting energy demand has been a critical process in various decision support systems
regarding consumption planning, distribution strategies, and energy policies. Traditionally …
regarding consumption planning, distribution strategies, and energy policies. Traditionally …
[HTML][HTML] Suspicious trading in nonfungible tokens (NFTs)
I Sifat, SA Tariq, D van Donselaar - Information & Management, 2024 - Elsevier
This paper employs a three-pronged approach to examine price patterns in a substantial
chunk of trades in nonfungible token (NFT) transactions to identify suspicious trading …
chunk of trades in nonfungible token (NFT) transactions to identify suspicious trading …