Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
An Improved Fastslam Framework Using Soft Computing, Ramazan Havangi, Mohammad Ali Nekoui, Mohammad Teshnehlab
An Improved Fastslam Framework Using Soft Computing, Ramazan Havangi, Mohammad Ali Nekoui, Mohammad Teshnehlab
Turkish Journal of Electrical Engineering and Computer Sciences
FastSLAM is a framework for simultaneous localization and mapping (SLAM) using a Rao-Blackwellized particle filter. However, FastSLAM degenerates over time. This degeneracy is due to the fact that a particle set estimating the pose of the robot loses its diversity. One of the main reasons for losing particle diversity in FastSLAM is sample impoverishment. In this case, most of the particle weights are insignificant. Another problem of FastSLAM relates to the design of an extended Kalman filter (EKF) for the landmark position's estimation. The performance of the EKF and the quality of the estimation depend heavily on correct a priori …
A Modified Particle Swarm Optimization Algorithm And Its Application To The Multiobjective Fet Modeling Problem, Ufuk Özkaya, Fi̇li̇z Güneş
A Modified Particle Swarm Optimization Algorithm And Its Application To The Multiobjective Fet Modeling Problem, Ufuk Özkaya, Fi̇li̇z Güneş
Turkish Journal of Electrical Engineering and Computer Sciences
This paper introduces a modified particle swarm algorithm to handle multiobjective optimization problems. In multiobjective PSO algorithms, the determination of Pareto optimal solutions depends directly on the strategy of assigning a best local guide to each particle. In this work, the PSO algorithm is modified to assign a best local guide to each particle by using minimum angular distance information. This algorithm is implemented to determine field-effect transistor (FET) model elements subject to the Pareto domination between the scattering parameters and operation bandwidth. Furthermore, the results are compared with those obtained by the nondominated sorting genetic algorithm-II. FET models are …
Multiobjective Fet Modeling Using Particle Swarm Optimization Based On Scattering Parameters With Pareto Optimal Analysis, Fi̇li̇z Güneş, Ufuk Özkaya
Multiobjective Fet Modeling Using Particle Swarm Optimization Based On Scattering Parameters With Pareto Optimal Analysis, Fi̇li̇z Güneş, Ufuk Özkaya
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, design-oriented field effect transistor (FET) models are produced. For this purpose, FET modeling is put forward as a constrained, multiobjective optimization problem. Two novel methods for multiobjective optimization are employed: particle swarm optimization (PSO) uses the single-objective function, which gathers all of the objectives as aggregating functions; and the nondominated sorting genetic algorithm-II (NSGA-II) sorts all of the trade-off solutions on the Pareto frontiers. The PSO solution is compared with the Pareto optimum solutions in the biobjective plane and the success of the first method is verified. Furthermore, the resulting FET models are compared with similar FET …
Discrete Particle Swarm Optimization For The Team Orienteering Problem, Ai̇şe Zülal Şevkli̇, Fati̇h Erdoğan Sevi̇lgen
Discrete Particle Swarm Optimization For The Team Orienteering Problem, Ai̇şe Zülal Şevkli̇, Fati̇h Erdoğan Sevi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel discrete particle swarm optimization (PSO) algorithm is proposed to solve the team orienteering problem (TOP). Discrete evaluation is achieved by redefining all operators and operands used in PSO. To obtain better results, a strengthened PSO, which improves both exploration and exploitation during the search process, is employed. Our algorithm achieves the best known solutions in a short time compared to previous heuristics for the TOP.