M Wang, H Ku - Expert Systems with Applications, 2021 - Elsevier
Corporate credit rating assessment is one of the crucial problems of credit risk management; it will help the financial institutions and government decide whether to issue debts. Recent …
S Kamley, S Jaloree, RS Thakur - International Journal of Electrical …, 2016 - academia.edu
Forecasting share performance becomes more challenging issue due to the enormous amount of valuable trading data stored in the stock database. Currently, existing forecasting …
S Kumar Chandar - Journal of Ambient Intelligence and Humanized …, 2019 - Springer
Stock market prediction is one of the most important financial subjects that have drawn researchers' attention for many years. Several factors affecting the stock market make stock …
A Al Nasseri, A Tucker, S De Cesare - Expert systems with applications, 2015 - Elsevier
Growing evidence is suggesting that postings on online stock forums affect stock prices, and alter investment decisions in capital markets, either because the postings contain new …
T Manojlović, I Štajduhar - 2015 38th International Convention …, 2015 - ieeexplore.ieee.org
Stock market prediction is considered to be a challenging task for both investors and researchers, due to its profitability and intricate complexity. Highly accurate stock market …
Stock market prediction is the challenging area for the investors to yield profits in the financial markets. The investors need to understand the financial markets which are more …
S Jabin - International Journal of Computer Applications, 2014 - researchgate.net
This paper presents computational approach for stock market prediction. Artificial Neural Network (ANN) forms a useful tool in predicting price movement of a particular stock. In the …
In the last 5 years, the availability of large audio datasets in African countries has opened unlimited opportunities to build machine intelligence (MI) technologies that are closer to the …
L Liu, Z Pei, P Chen, H Luo, Z Gao, K Feng… - International Journal of …, 2023 - Springer
Deep learning has achieved tremendous success in various applications owing to its robust feature representations of complex high-dimensional nonlinear data. Financial time-series …