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IEEE Conference on Computer Vision and Pattern Recognition

作者： Masaki Saito Takayuki Okatani Koichiro Deguchi Tohoku University Japan

ISBN: (纸本)9781467364102

This paper is concerned with the inference of marginal densities based on MRF models. The optimization algorithms for continuous variables are only applicable to a limited number of problems, whereas those for discrete variables are versatile. Thus, it is quite common to convert the continuous variables into discrete ones for the problems that ideally should be solved in the continuous domain, such as stereo matching and optical flow estimation. In this paper, we show a novel formulation for this continuous-discrete conversion. The key idea is to estimate the marginal densities in the continuous domain by approximating them with mixtures of rectangular densities. Based on this formulation, we derive a mean field (MF) algorithm and a belief propagation (BP) algorithm. These algorithms can correctly handle the case where the variable space is discretized in a non-uniform manner. By intentionally using such a non-uniform discretization, a higher balance between computational efficiency and accuracy of marginal density estimates could be achieved. We present a method for actually doing this, which dynamically discretizes the variable space in a coarse-to-fine manner in the course of the computation. Experimental results show the effectiveness of our approach.

关键词： problems efficiency accuracy discrete transforms Traffic estimation optimization algorithms Computational efficiency

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The Computation of Full-complexity Polytopic Robust Control Invariant Sets

The Computation of Full-complexity Polytopic Robust Control ...

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IEEE Annual Conference on Decision and Control

作者： Chengyuan Liu Imad M. Jaimoukha Department of Electrical and Electronic Engineering Imperial College London SW7 2AZ UK

ISBN: (纸本)9781479978878

This paper considers the problem of evaluating robust control invariant (RCI) sets for linear discrete-time systems subject to state and input constraints as well as additive disturbances. An RCI set has the property that if the system state is inside the set at any one time, then it is guaranteed to remain in the set for all future times using a predefined state feedback control law. This problem is important in many control applications. We present a numerically efficient algorithm for the computation of full-complexity polytopic RCI sets. Farkas' Theorem is first used to derive necessary and sufficient conditions for the existence of an admissible polytopic RCI set in the form of nonlinear matrix inequalities. An Elimination Lemma is then used to derive sufficient conditions, in the form of linear matrix inequalities, for the existence of the solution. An optimization algorithm to approximate maximal RCI sets is also proposed. Numerical examples are given to illustrate the effectiveness of the proposed algorithm.

关键词： SETTING Sufficient conditions Robust control state feedback control Invariant linear matrix inequalities optimization algorithms

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Novel Spiral Antennas Design Using Swarm Intelligence for Passive UHF RFID Tags

Novel Spiral Antennas Design Using Swarm Intelligence for Pa...

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European Conference on Antennas and Propagation

作者： Sotirios K. Goudos Katherine Siakavara John N. Sahalos Radiocommunications Laboratory: Department of Physics Aristotle University of Thessaloniki Thessaloniki Greece Radio & Telecommunications Lab: Department of Electrical and Computer Engineering University of Nicosia Cyprus

ISBN: (纸本)9781467321877

In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial EM software. Furthermore, a theoretical analysis of the spiral antennas was performed. The input impedance of the printed spiral, was calculated approximately via the Transmission Line Model and the electromotive force induced along the spirals. The theoretical results seem to be in good agreement with the EM solver results. The optimization results produced show that ABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems. RFID tags with dimensions less than 4cm, gain that reaches the value of 2 dBi and read distance about 11.7m were among those obtained by the algorithm.

关键词： RFID tags Helical antennas Particle swarm optimization Passive RFID tags TRANSMISSION LINE MODELLING impedance optimization algorithms UHF band Spiral

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A Nonlinear Estimator Concept for Active Vehicle Suspension Control

A Nonlinear Estimator Concept for Active Vehicle Suspension ...

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American Control Conference

作者： Guido Koch Tobias Kloiber Enrico Pellegrini Boris Lohmann Institute of Automatic Control Technische Universitat Munchen 86748 Garching Germany

ISBN: (纸本)9781424474264

A new Kalman filter based signal estimation concept for active vehicle suspension control is presented in this paper considering the nonlinear damper characteristic of a vehicle suspension setup. The application of a multi-objective genetic optimization algorithm for the tuning of the estimator shows that three parallel Kalman filters enhance the estimation performance for the variables of interest (states, dynamic wheel load and road profile). The Kalman filter structure is validated in simulations and on a testrig for an active suspension configuration using measurements of real road profiles as disturbance input. The advantages of the concept are its low computational effort compared to Extended or Unscented Kalman filters and its good estimation accuracy despite the presence of nonlinearities in the suspension setup.

关键词： Automobile suspensions Kalman filters nonlinearity Road optimization algorithms

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Revisiting Local PageRank Estimation on Undirected Graphs: Simple and Optimal

arXiv

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arXiv 2024年

作者： Wang, Hanzhi Renmin University of China Beijing China

We propose a simple and optimal algorithm, BackMC, for local PageRank estimation in undirected graphs: given an arbitrary target node t in an undirected graph G comprising n nodes and m edges, BackMC accurately estimates the PageRank score of node t while assuring a small relative error and a high success probability. The worst-case computational complexity of BackMC is upper bounded by (formula presented) , where dmin denotes the minimum degree of G, and dt denotes the degree of t, respectively. Compared to the previously best upper bound of (formula presented) (VLDB’23), which is derived from a significantly more complex algorithm and analysis, our BackMC improves the computational complexity for this problem by a factor of (formula presented) with a much simpler algorithm. Furthermore, we establish a matching lower bound of (formula presented) for any algorithm that attempts to solve the problem of local PageRank estimation, demonstrating the theoretical optimality of our BackMC. We conduct extensive experiments on various large-scale real-world and synthetic graphs, where BackMC consistently shows superior performance. Copyright © 2024, The Authors. All rights reserved.

关键词： optimization algorithms

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Mining Potentially Explanatory Patterns via Partial Solutions

arXiv

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arXiv 2024年

作者： Catalano, GianCarlo A.P.I. Brownlee, Alexander E.I. Cairns, David McCall, John Ainslie, Russell University of Stirling Computing Science and Mathematics Stirling United Kingdom Robert Gordon University National Subsea Centre Aberdeen United Kingdom BT Technology Applied Research Ipswich United Kingdom

Genetic algorithms have established their capability for solving many complex optimization problems. Even as good solutions are produced, the user’s understanding of a problem is not necessarily improved, which can lead to a lack of confidence in the results. To mitigate this issue, explainability aims to give insight to the user by presenting them with the knowledge obtained by the algorithm. In this paper we introduce Partial Solutions in order to improve the explainability of solutions to combinatorial optimization problems. Partial Solutions represent beneficial traits found by analyzing a population, and are presented to the user for explainability, but also provide an explicit model from which new solutions can be generated. We present an algorithm that assembles a collection of Partial Solutions chosen to strike a balance between high fitness, simplicity and atomicity. Experiments with standard benchmarks show that the proposed algorithm is able to find Partial Solutions which improve explainability at reasonable computational cost without affecting search performance. © 2024, CC BY.

关键词： optimization algorithms

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SMALL PERTURBATION ANALYSIS OF NETWORK TOPOLOGIES

SMALL PERTURBATION ANALYSIS OF NETWORK TOPOLOGIES

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Elena Ceci Sergio Barbarossa Dept. of Information Engineering Electronics and Telecommunications Sapienza University of Rome Via Eudossiana 18 00184 Rome Italy

ISBN: (纸本)9781538646595

The goal of this paper is to derive a small perturbation analysis for networks subject to random changes of a small number of edges. Small perturbation theory allows us to derive, albeit approximate, closed form expressions that make possible the theoretical statistical characterization of the network topology changes. The analysis is instrumental to formulate a graph-based optimization algorithm, which is robust against edge failures. In particular, we focus on the optimal allocation of the overall transmit powers in wireless communication networks subject to fading, aimed at minimizing the variation of the network connectivity, subject to a constraint on the overall power necessary to maintain network connectivity.

关键词： Graph topologies network reliability information flow small perturbation analysis information flow small disturbance Network Network topology perturbation Wireless networks Transmitter power optimal allocation optimization algorithms fading color

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A comparative study of Improved Bat Algorithm and Bat Algorithm on numerical benchmarks

A comparative study of Improved Bat Algorithm and Bat Algori...

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International Conference on Advanced Computer Science Applications and Technologies

作者： Mehmet BESKIRLI Ismail KOC Department of Computer Engineering Engineering Faculty Selcuk University

ISBN: (纸本)9781509004256

optimization is employed in solutions of many problems today. optimization is described as finding the most suitable alternative among many others under the given constraints. Meta-heuristic algorithms used in solutions of the problems are developed upon the behaviors of living creatures in the nature. One of these is Bat Algorithm (BA), an optimization method based on swarm intelligence. BA is a numerical optimization technique developed in recent times. In this paper, it is aimed at improving Bat Algorithm (IBA) by using Differential Evolution Algorithm population strategy instead of population generation method of BA. IBA was tested on 17 benchmark functions with different characteristics. Suggested method has been seen to exhibit better results compared to the original BA.

关键词： Bat Algorithm Benchmark Functions Improved Bat Algorithm Swarm Intelligence optimization algorithms

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Electrostatic Discharge Algorithm for Economic Load Dispatch Problems Including Renewable Energy

Electrostatic Discharge Algorithm for Economic Load Dispatch...

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Sustainable Technology and Engineering Applications (NCETSTEA), 2020 National Conference on Emerging Trends on

作者： Saikat Nandy Provas Kumar Roy M.Tech in Electrical Engineering Kalyani Govt. Engineering College Kalyani India Dept. of Electrical Engineering Kalyani Govt. Engineering College Kalyani India

ISBN: (数字)9781728143620

ISBN: (纸本)9781728143637

This article approaches about electrostatic discharge algorithm (ESDA) which is applied to find the optimization problems of economic load dispatch (ELD). This algorithm is tested and applied for the systems of 6 and 40 units. Wind power is included with the both systems for minimizing the cost. Now-a-days wind energy is getting more importance because wind energy is easily accessible all over the world. Both units of 6 and 40 are tested with and without wind energy respectively. The tested results are compared with the recent available optimization algorithms and electrostatic discharge algorithm proves itself as more effective optimization technique than others.

关键词： Eltrostatic Discharge algorithm Economic load dispatch renewable energy Renewable energy load dispatching Wind energy electrostatic discharge optimization algorithms algorithms

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Comparison of Different PSO Initialization Techniques for High Dimensional Search Space Problems: A Test with FSS and Antenna Arrays

Comparison of Different PSO Initialization Techniques for Hi...

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European Conference on Antennas and Propagation

作者： A. L. Gutierrez M. Lanza I. Barriuso L. Valle M. Domingo J. R. Perez J. Basterrechea Dpto. Ingenieria de Comunicaciones Universidad de Cantabria Laboratorios I+D de Telecomunicaciones

ISBN: (纸本)9781457702501

Population-based optimization algorithms are widely used in multiple research areas to optimize different kinds of problems. Commonly, they have been successfully applied to low and medium size search spaces in order to tune or adjust several design parameters. Unfortunately, population-based algorithms can require too much CPU time to find a nearly optimal solution as the number of dimensions of the problem to tackle increases significantly. Usually, mathematical or physical-inspired techniques have been applied to improve the success rate as well as the speed of convergence of population-based methods in a high dimensional framework. An alternative choice is to allocate the individuals of the population in an efficient way during the initialization stage of the algorithm considering two possibilities: placing individuals as close as possible to a global optimum or uniformly distributed over the search space. In this work, three different initialization strategies, the orthogonal array initialization, a chaotic technique and the opposition based initialization have been considered and appropriately combined with the heuristic particle swarm optimization (PSO) algorithm. Results comparing the modified PSO algorithm when applied to optimize frequency selective surfaces (FSS) and planar arrays for WiMAX applications are included.

关键词： initialization frequency selective surfaces Antenna arrays parametric subharmonic oscillator Planar antennas global optimum DIMENSIONAL optimization algorithms CPU time Gegenhalten

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