Identification of linear parameter varying models is considered in the paper, under the assumption that both the output and the scheduling parameter measurements are affected by bounded noise. First, the problem of computing parameter uncertainty intervals is formulated in terms of nonconvex optimization. Then, on the basis of the analysis of the regressor structure, we present an ad hoc convex...

Particle swarm optimization is a metaheuristic technique widely applied to solve various optimization problems as well as parameter selection problems for various classification techniques. This paper presents an approach for linear support vector machines classifier optimization combining its selection from a family of similar classifiers with parameter optimization. Experimental results indic...

a compact formulation of the set of tours neither in a graph nor its complement is presented and illustrates a general methodology proposed for constructing polyhedral models of decision problems based upon permutations, projection and lifting techniques. directed hamilton tours on n vertex graphs are interpreted as (n-1)- permutations. sets of extrema of birkhoff polyhedra are mapped to tours ...

Incremental linearization is a conceptually simple, yet effective, technique that we have recently proposed for solving SMT problems on the theories of non-linear arithmetic over reals and integers. Optimization Modulo Theories (OMT) an important extension which allows finding models optimize given objective functions. In this paper, show how incremental can be extended to OMT in simple way, pr...

0950-7051/$ see front matter 2012 Elsevier B.V. A http://dx.doi.org/10.1016/j.knosys.2012.08.015 ⇑ Corresponding author. Tel.: +86 15811424568; fa E-mail address: [email protected] (S. Guo). Accurate annual power load forecasting can provide reliable guidance for power grid operation and power construction planning, which is also important for the sustainable development of electric power indus...

In this paper, a new identification technique is introduced to estimate a linear fractional representation of a linear parameter-varying (LPV) system from local experiments by using a dedicated non-smooth optimization procedure. More precisely, the developed approach consists in estimating the parameters of an LPV state-space model from local fullyparameterized identified state-space models thr...

Probabilistic finite automata (PFA) are recognizers of regular distributions over strings, a model that is widely applied in speech recognition and biological systems, for example. While the underlying structure PFA just normal automaton, it well known with non-deterministic more powerful than deterministic one. In this paper, we concentrate on passive learning from examples counterexamples usi...

In this study, we analysed the thermal performance, thermal stability and optimum design analyses of a longitudinal, rectangular fin with temperature-dependent, thermal properties and internal heat generation under multi-boiling heat transfer using Haar wavelet collocation method. The effects of the key and controlling parameters on the thermal performance of the fin are investigated. The therm...

In this paper, a new identification technique is introduced to estimate a linear fractional representation of a linear parameter-varying (LPV) system from local experiments by using a dedicated non-smooth optimization procedure. More precisely, the developed approach consists in estimating the parameters of an LPV state-space model from local fullyparameterized identified state-space models thr...