. Particle swarm optimization (PSO) and Imperialist competitive algorithm (ICA) are the two props used to get the optimal PID gains. ICA proves to be more robust than PSO in performing optimal transient performance even under various nominal operating conditions. Computational time required by PSO is more

We deal with the competitive analysis of algorithms for managing data in a distributed environment. We deal with the file allocation problem ([DF], [ML]), where copies of a file may be be stored in the local storage of some subset of processors. Copies may be replicated and discarded over time

We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular

must contain at most one assigned code. In this paper, we focus on the online version of the OVSF code assignment problem and give a 10-competitive algorithm (where the cost is measured by the total number of assignments and reassignments used). Our algorithm improves the previous O(h)competitive

of the competitive ratio is O(log h), then give an online algorithm with competitive ratio O(log h); if h is not known in advance, we give an online algorithm with competitive ratio O(h 3log−1/2 h 1

document without permission of its author may be prohibited by law.

have proposed a family of algorithms based on a simple psychological mechanism: onereason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the authors held a competition

of the decision-tree algorithm C4.5. The experiments show that in situations with little or no classification noise, randomization is competitive with (and perhaps slightly superior to) bagging but not as accurate as boosting. In situations with substantial classification noise, bagging is much better than

FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the hardware in order to maximize performance. This paper shows that such an approach can yield an implementation that is competitive with hand-optimized libraries, and describes the software structure that makes our