The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A new filtering algorithm - PSO-PF was proposed for nonlinear dynamic systems. Basing on the concept of re-sampling, particles with bigger weights should be re-sampled more time, and in the PSO-PF, after calculating the weight of particles, some particles will join in the refining process, which means that these particles will move to the region with higher weights. This process can be regarded as...
A new filtering algorithm - PSO-UPF was proposed for nonlinear dynamic systems. Basing on the concept of re-sampling, particles with bigger weights should be re-sampled more time, and in the PSO-UPF, after calculating the weight of particles, some particles will join in the refining process, which means that these particles will move to the region with higher weights. This process can be regarded...
With many advantages of computing with real number, few parameters to be adjusted, the Particle Swarm Optimizer (PSO) is applied in many fields. The major problem with PSO algorithm is premature convergence. Some optimization strategies were introduced to overcome it. In these former researches, the dimension of benchmarks in experiments was usually set to be a small value. But it can be seen that...
This paper presents a dynamic mutation particle swarm optimization (DMPSO). The particle swarm optimization (PSO) is a popular swarm algorithm, which has exhibited good performance on many optimization problems. However, similar to other swarm intelligence algorithms, PSO also suffers from premature convergence. Sub swarm and mutation are widely used strategies in the PSO algorithm to overcome the...
This paper presents a distance-guided particle swarm optimizer with dynamic mutation (PSODM). Two characteristics are proposed in the PSODM: distance-guided and dynamic mutation. The goal of these characteristics is to overcome premature convergence of the swarm and accelerating the convergence velocity. With distance-guided operation, some particles too intense can be separated, while with dynamic...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.