Introduction -- Application of Data Mining Methods for Pattern Recognition in Negotiation Support Systems -- Advanced Maintenance of Data Richness in Business Communication Data – An Evaluation of Dimensionality Reduction Techniques -- Analytical Comparison of Clustering Techniques for the...

In this study, we apply several advanced machine learning techniques including extreme gradient boosting (XGBoost), support vector machine (SVM), and a deep neural network to predict bankruptcy using easily obtainable financial data of 3728 Belgian Small and Medium Enterprises (SME’s) during...

The future is unknown and uncertain, but there are ways to predict future events and reap the rewards safely. One such opportunity is the application of machine learning and artificial intelligence for stock market prediction. The stock market is turbulent, yet using artificial intelligence to...

Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature. This paper aims to construct robust support vector machine classifiers under feature data...

Machine learning (ML) is a new-age thriving technology, which facilitates computers to read and interpret from the previously present data automatically. It makes use of multiple algorithms to build models, mathematical in nature, and then makes predictions for the new data using the past data...

AbstractSoil moisture (SM) of maize has an extremely important impact on the growth and development of maize. Therefore, predicting the SM of maize will become extremely important, guiding the management of agricultural irrigation and water resources. This paper, therefore, proposes a new hybrid...

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The modeling of logistic disability inception probabilities is formulated as a support vector regression problem. Using a quantum feature map, the data are mapped to quantum...

We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016, European Journal of Political Economy). Four improvements are particularly notable: First, we produce a...

The impact the last financial crisis had on the small- and medium-sized enterprises (SMEs) sector varied across countries, affecting them on different levels and to a different extent. The economic situation in Poland during and after the financial crisis was quite stable compared to other EU...

We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016, European Journal of Political Economy). Four improvements are particularly notable: First, we produce a...

This study introduces the Ensemble Empirical Mode Decomposition (EEMD) technique to forecasting popular vote share. The technique is useful when using polling data, which is pertinent when none of the main candidates is the incumbent. Our main interest in this study is the short- and long-term...

As the Internet is rising at a rapid pace, cyber attacks have also increased as a result. There is a rapid rise in the form and rate of incidence of these attacks. There are several conventional security solutions that exist, but in the case of big data, these solutions do not work well. Instead...

The purpose of this study is twofold. First, causal mechanisms underlying the effect of changing attitudes on behavioral change are investigated. Second, recommendations are presented to improve the understanding of how attitudes and behavioral patterns of energy consumption in the residential...

For easy payment and classless Credit card payment has become very popular these days. From our bank account we can directly pay the amount online. In spite of this easy payment method it has the disadvantage of having frauds. The unauthorized person accessing the bank details of other person is...

If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ecological rationality. The main casualty of...

Cloud computing hastens technology driven innovation by taking advantage of the speed, the cost-effectiveness, the efficiency and the security that such applications offer. By using cloud computing, public organizations can exploit the economies of scale and innovate both efficiency and rapidly....

Bankruptcy prediction is always a topical issue. The activities of all business entities are directly or indirectly affected by various external and internal factors that may influence a company in insolvency and lead to bankruptcy. It is important to find a suitable tool to assess the future...

Electricity markets are considered to be the most volatile amongst commodity markets. The non-storability of electricity and the need for instantaneous balancing of demand and supply can often cause extreme short-lived fluctuations in electricity prices. These fluctuations are termed price...

The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions,...

Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...

We present a general supervised machine-learning methodology to represent the payment behavior of financial institutions starting from a database of transactions in the Colombian large-value payment system. The methodology learns a feedforward artificial neural network parameterization to...

Data mining is a technical analysis for the massive database with meaning full output. Churn analysis is best applications for the data mining able to determine the behavior of the customer in changing different services. The available marketing tool has the limitation to predict the changing...

The aim of this paper is to investigate the Support Vector Machine (SVM), the Binary Gravity Search Algorithm combined Support Vector Machine (BGSA-SVM), the Multi-layer Perceptron (MLP), the Convolution Neural Network (CNN) and the Long Short-Term Memory (LSTM) neural network, when applied to...

Currency counterfeiting is a serious crime that affects a country's finances. The proposed system will be useful to detect counterfeit banknotes in banking systems. India is facing more serious problems due to the increase in fake notes in the market. To get rid of this problem, various fake...

In 1983, Meese and Rogoff showed that traditional economic models developed since the 1970s do not perform better than the random walk in predicting out-of-sample exchange rates when using data obtained after the beginning of the floating rate system. Subsequently, whether traditional economical...