We describe how CiPF 2.0, a propositional constructive learner, can cope with both noise and representation mismatch in training examples simultaneously. CiPF 2.0 abilities stem from coupling the robust selective learner C4.5 (and its production rule generator) with a sophisticated constructive induction component. An important new general constructive operator incorporated into CiPF 2.0 is the...

We consider the first Dirichlet eigenvalue problem for a mixed local/nonlocal elliptic operator and we establish quantitative Faber-Krahn inequality. More precisely, show that balls minimize among sets of given volume provide stability result almost attain minimum.

In this paper, we introduce a nature inspired meta-heuristic for scheduling jobs on computational grids. Our approach is to dynamically generate an optimal schedule so as to complete the tasks in a minimum period of time as well as utilizing the resources in an efficient way. The approach proposed is a variant of particle swarm optimization which uses mutation operator. The mutation operator ca...

This brief presents the derivation of an arbitrary order delta operator-based direct-form IIR filter with minimum roundoff noise gain and sensitivity. It utilizes the concept of different coupling coefficients at different branch nodes for better noise gain suppression. Two possible structures for realizing the inverse delta operator are considered and procedures for calculating the optimal fil...

We construct a Banach space operator T which is not E(T)subscalar but ‖(T − z)−1‖ ≤ (|z| − 1)−1 for |z| > 1 and m(T − z) ≥ const · (1 − |z|)3 for |z| < 1 (here m denotes the minimum modulus). This gives a negative answer to a variant of a problem of Laursen and Neumann. We also give a sufficient condition (in terms of growth of resolvent and of an analytic left inverse of T − z) implying that T...

In this paper a class of bottleneck combinatorial optimization problems with uncertain costs is discussed. The uncertainty is modeled by specifying a discrete scenario set containing a finite number of cost vectors, called scenarios. In order to choose a solution the Ordered Weighted Averaging aggregation operator (shortly OWA) is applied. The OWA operator generalizes traditional criteria in de...

The Set Covering Problem is a formal model for many practical optimization problems. It consists in finding a subset of columns in a zero/one matrix such that they cover all the rows of the matrix at a minimum cost. To solve the Set Covering Problem we will use a metaheuristic called Fireworks Algorithm (FWA) inspired by the fireworks explosion. Through the observation of the way that fireworks...

This paper is concerned with the determination of optimal sensor locations for structural modal identification in a strap-braced cold formed steel frame based on an improved genetic algorithm (IGA). Six different optimal sensor placement performance indices have been taken as the fitness functions two based on modal assurance criterion (MAC), two based on maximization of the determinant of a Fi...

To solve the Set Covering Problem we will use a metaheuristic Fireworks Algorithm inspired by the fireworks explosion. Through the observation of the way that fireworks explode is much similar to the way that an individual searches the optimal solution in swarm. Fireworks algorithm (FWA) consists of four parts, i.e., the explosion operator, the mutation operator, the mapping rule and selection ...

We propose a nonlinear edge detection technique based on a two concentric circular windows operator. We perform a preliminary selection of edge candidates using standard gradient and use the dual window operator to reveal edges as zero-crossing points of a simple difference function only depending on the minimum and maximum values in the two windows. Comparisons with other well-established tech...