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Amal Al Ali, Ahmed M. Khedr, Magdi El Bannany and Sakeena Kanakkayil
Despite the obvious benefits and growing popularity of Machine Learning (ML) technology, there are still concerns regarding its ability to provide Financial Distress Prediction (FDP). An accurate FDP model is required to avoid financial risk at the lowes...
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Ashish Sedai, Rabin Dhakal, Shishir Gautam, Anibesh Dhamala, Argenis Bilbao, Qin Wang, Adam Wigington and Suhas Pol
The Machine Learning/Deep Learning (ML/DL) forecasting model has helped stakeholders overcome uncertainties associated with renewable energy resources and time planning for probable near-term power fluctuations. Nevertheless, the effectiveness of long-te...
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Abdellilah Nafia, Abdellah Yousfi and Abdellah Echaoui
In recent years, a great deal of attention has been devoted to the use of neural networks in portfolio management, particularly in the prediction of stock prices. Building a more profitable portfolio with less risk has always been a challenging task. In ...
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Muhamad Jumaa, Mohammed Saqib, Arif Attar
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Khalid Abbas, Ahmed Eltweri, Muhammad Kamran Nawaz and Zafar Ali
The aim of this study is to provide an examination of the factors that have a bearing on KSB, based upon attitudes amongst academics in developing countries, using a particular focus upon academics within the University of Baghdad. With the research stud...
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