Both academic and nonacademic literature is evolving following the oscillating development
of artificial intelligence (AI) and computing power's evolution in their application to finance …

The bankruptcy prediction research domain continues to evolve with many new different
predictive models developed using various tools. Yet many of the tools are used with the …

Mining industry is the basic industry of the national economy. However, in recent years,
listed mining companies have suffered serious financial risks due to special reasons such as …

As a hot topic, financial distress prediction (FDP), or called as corporate failure prediction,
bankruptcy prediction, acts as an important role in decision-making of various areas …

Recently, artificial intelligence technologies have received considerable attention because
of their practical applications in various fields. The key factor in this prosperity is deep …

Nowadays, many current real financial applications have nonlinear and uncertain behaviors
which change across the time. Therefore, the need to solve highly nonlinear, time variant …

For financial institutions, the ability to predict or forecast business failures is crucial, as
incorrect decisions can have direct financial consequences. Bankruptcy prediction and …

Feature selection and instance selection are two important data preprocessing steps in data
mining, where the former is aimed at removing some irrelevant and/or redundant features …

Corporate bankruptcy prediction is very important for creditors and investors. Most literature
improves performance of prediction models by developing and optimizing the quantitative …

Feature selection is an important preprocessing step in machine learning and pattern
recognition. The ultimate goal of feature selection is to select a feature subset from the …