The optimization problems occurring in nonlinear regression normally cannot be proven unimodal. In the present paper applicability of global optimization algorithms to this problem is investigated with the focus on interval arithmetic based algorithms.

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity mode...

In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system (FLS). In order to make the type-2 FLS reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and probability type reduce reasoning method for the interval-valued FLS are developed. We have...

We introduce the notion of arithmetic progression blocks or m-AP-blocks of Zn, which can be represented as sequences of the form (x, x+m,x+2m, . . . , x+ (i−1)m) (mod n). Then we consider the problem of partitioning Zn into m-APblocks. We show that subject to a technical condition, the number of partitions of Zn into m-AP-blocks of a given type is independent of m, and is equal to the cyclic mu...

emphasis on milk yield (my) as well as milk yield persistency (myp) and calving interval (ci) is necessary to achieve more sustainable productionin dairy cattle. therefore the main objective of this study was to find an optimum regression model to estimate economic values for my, myp and ci.using a deterministic bio-economic model, seventyfiveproduction states differing mainly in my, mypand ciw...