This study proposes a new complex system modeling approach by extending a bias-variance trade-off into a bias-variance-complexity trade-off framework. In the framework, the computational complexity is introduced for system modeling. For testing purposes, complex financial system data are used for modeling. Empirical results obtained reveal that this novel approach performs well in complex syste...

Uncertainty theory is a branch of axiomatic mathematics that deals with human uncertainty, and uncertain variable is used tomodel the uncertain quantities. Inverse uncertainty distribution provides an easy way to calculate the functions of uncertain variables as well as their expected values. This paper mainly presents a formula to calculate the variance of an uncertain variable via the inverse...

Wavelets have recently been a subject of great interest in geophysics, mathematics and signal processing. The discrete wavelet transform can be used to decompose a time series with respect to a set of basis functions, each one of which is associated with a particular scale. The properties of a time series at different scales can then be summarized by the wavelet variance, which decomposes the v...

A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the benefits of the plain clustering algorithm with regard to other approaches for clustering. Experiments using both synthetic and real data have been performed in order to evaluate the differences between the proposed me...

The authors investigated predictors of supervisor-targeted workplace aggression among 105 "moonlighters" (employed adults who work 2 jobs, each with a different supervisor), as a way of examining the relative role played by within-subject situational differences and between-subjects individual differences. Individual difference variables (self-esteem, history of aggression) explained a similar ...