In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...

We present an efficient method for selecting important input variables when building a fuzzy model from data. Past methods for input variable selection require generating different models while searching for the optimal combination of variables; our method requires generating only one model that employs all possible input variables. To determine the important variables, premises in the fuzzy ru...

We introduce the essential inputs (variables) for terms (trees) and tree automata. It is proved that if an input xi is essential for a tree t and an automaton A then there is a chain of subtrees connecting xi with the root of t such that xi is essential for each subtree belonging to this chain. There are investigations which treat some rules for removing and adding of fictive (non-essential) in...

In this paper, the problem of identifying stochastic linear continuous-time systems from noisy input/output data is addressed. The input of the system is assumed to have a skewed probability density function, whereas the noises contaminating the data are assumed to be symmetrically distributed. The third-order cumulants of the input/output data are then (asymptotically) insensitive to the noise...