This paper proposes, focusing on random forests, the increasingly used statistical method for classification and regression problems introduced by Leo Breiman in 2001, to investigate two classical issues of variable selection. The first one is to find important variables for interpretation and the second one is more restrictive and try to design a good prediction model. The main contribution is...

The leader–follower consensus of a class variable-order fractional (VOF) uncertain linear multi-agent systems is studied in this paper. Firstly, new general lemma proposed to find Lyapunov candidate functions for the stability VOF systems. Secondly, according and theorem systems, by using singular value decomposition matrices some related lemmas, sufficient condition obtain given form matrix in...

We propose and analyze a numerical method for time-dependent linear Schrödinger equations with uncertain parameters in both the potential initial data. The random are discretized by stochastic collocation on sparse grid, sample solutions nodes approximated Strang splitting method. computational work is reduced multilevel strategy, i.e., combining information obtained from computed different ref...

Probabilistic logic and credibilistic logic are two branches of multi-valued logic for dealing with random knowledge and fuzzy knowledge, respectively. In this paper, a hybrid logic is introduced for dealing with random knowledge and fuzzy knowledge simultaneously. First, a hybrid formula is introduced on the basis of random proposition and fuzzy proposition. Furthermore, a hybrid truth value i...

This paper is concerned with the robust finitehorizon filtering problem for a class of uncertain nonlinear discrete time-varying stochastic systems with multiple missing measurements and error variance constraints. All the system parameters are time-varying and the uncertainty enters into the state matrix. The measurement missing phenomenon occurs in a random way, and the missing probability fo...

This paper is on Fuzzy Stochastic Optimisation, an area that is quickly coming to the forefront of mathematical programming under uncertainty. An even stronger motivating factor for the growing interest in this area can be found in the ubiquitous nature of decision problems involving hybrid undeterminacy. More precisely, we consider a range of situations in which random factors and fuzzy inform...