In the automotive industry, cost estimation of components to be purchased plays an
important role for price negotiations with suppliers and, therefore, for cost control within the …

Our recently developed CMARS is powerful in handling complex and heterogeneous data.
We include into CMARS the existence of uncertainty about the scenarios. Indeed, data …

In this paper, are explored and analyzed time series and machine learning models for
prediction of unemployment in several countries (Med, Baltic, Balkan, Nordic, Benelux) for …

Solving the problems related to air pollution is crucial for human health and the ecosystems
in many urban areas throughout the world. The accumulation of large arrays of data with …

Although the used car market in India is enormous, with an annual 27.1 billion USD worth of
car sales, no academic study examining the pricing of Indian used cars is available. The …

Since, with increased volatility and further uncertainties, financial crises translated a high
“noise” within data from financial markets and economies into the related models, recent …

This study aims at critically reviewing the research that has been conducted to improve the
backward part of the Multivariate Adaptive Regression Splines (MARS) method that leads to …

Climate change is becoming an ever important issue due to the possibility that it may result
in extreme weather events such as floods or droughts. Consequently, precipitation …

System dynamics is one of the widely used and instrumental approaches to solve different
types of real-time problems from different areas. System dynamics modelling is often the …

Earthquake research has not yielded promising results because earthquakes have
uncertain data parameters, and one of the methods to overcome the problem of uncertain …