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 amelioration Particle Swarm Optimization (SARPSO) based on simulated annealing (SA), asynchronously changed learning genes (ACLG) and roulette strategy was proposed because the classical Particle Swarm Optimization (PSO) algorithm was easily plunged into local minimums. SA had the ability of probability mutation in the search process, by which the search processes of PSO plunging into local...
The sociological background of particle swarm optimization is analyzed, and for preventing from premature convergence, a modified approach to enhance organizational management mechanism in group is proposed. Two sub-swarms evolutionary particle swarm optimization based on team progress learning is proposed by borrowing ideas from social division and progress learning ideas in management team. The...
In consideration of stagnation phenomenon in the later phase of the particle swarm optimization (PSO) caused by diversity scarcity of particles, a new learning strategy for improving the global and local exploration capability of particle swarm optimization is proposed in the paper. The new learning strategy is inspired by the mass migration behaviors of animal swarms that each individual has the...
The paper suggests a new modified approach to improve the performance of particle swarm optimization (PSO). Inspired by the intelligent behaviors of the natural biotic populations, the modified PSO is based on an adaptive strategy, the particle should stop the inertia movement to enhance the learning from its experiences and its neighbors when it is found to be in wrong searching direction, and stop...
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.