Stock market forecasting has been a challenging financial research topic for decades. In the
literature, there are numerous results based on point methods. However, poor forecasting …

Single factor (one-way) analysis of variance (ANOVA) has been very broadly applied in
analyzing experimental data with categorical treatments. Datasets to be analyzed with …

Crowdsourcing is an emerging paradigm in AI and machine learning. It involves gathering
input from human crowds, usually through the Internet, to solve a given task. Due to its open …

With inputs from human crowds, usually through the Internet, crowdsourcing has become a
promising methodology in AI and machine learning for applications that require human …

I consider the task of the so called curve fitting or experimental data fitting, commonly
encountered in various branches of scientific research and in engineering practice. Unlike …

Uncertainties in the real world often appear as variabilities of observed data under similar
conditions. In this paper, we use interval functions to model uncertainty and function …

This paper reports an interval least-squares (ILS) algorithm that computationally
approximates an interval function, in which both dependent and independent variables are …

I consider the task of experimental data fitting. Unlike the traditional approach I do not try to
minimize any functional based on available experimental information, instead the …

Using input collected from human crowds through the internet, crowdsourcing has rapidly
become an established method for solving applications requiring human input in artificial …

Fat enough straight line) Abstract: Introduction of interval calculus and methods to everyday
laboratory practice is encouraged. After a short presentation of basic facts from interval …