The global nature of the Czech economy means that quantitative knowledge of the influence of the exchange rate provides useful information for all participants in the international economy. Systematic and academic research show that the issue of estimating the Czech crown/Chinese yuan exchange...

This paper describes an objective way of predicting the likelihood of major league baseball players being elected to the Hall of Fame by members of the Baseball Writers' Association of America. A radial basis function (RBF) network is used to build separate machine learning models for pitchers...

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network....

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network....

The aim of this paper is to show that option prices in jump-diffusion models can be computed using meshless methods based on Radial Basis Function (RBF) interpolation instead of traditional mesh-based methods like Finite Differences (FDM) or Finite Elements (FEM). The RBF technique is...

In this paper, we solve the customer credit card churn prediction via data mining. We developed an ensemble system incorporating majority voting and involving Multilayer Perceptron (MLP), Logistic Regression (LR), decision trees (J48), Random Forest (RF), Radial Basis Function (RBF) network and...

We price multi-asset options by solving their price partial differential equations using a meshfree approach with radial basis functions under jump-diffusion and geometric Brownian motion frameworks. In the geometric Brownian motion framework, we propose an effective technique that breaks the...

A novel neural architecture for prediction in industrial control: the 'Double Recurrent Radial Basis Function network' (R2RBF) is introduced for dynamic monitoring and prognosis of industrial processes. Three applications of the R2RBF network on the prediction values confirmed that the proposed...

In this paper, we solve the customer credit card churn prediction via data mining. We developed an ensemble system incorporating majority voting and involving Multilayer Perceptron (MLP), Logistic Regression (LR), decision trees (J48), Random Forest (RF), Radial Basis Function (RBF) network and...

This study analyses the situation of a bank that wants to create an Internal Rating System (IRB). A credit institute can decide to simulate rating judgements from an external rating agency, like Standard and Poor's or Moody's or Fitch Rating. This research compares different frameworks of neural...