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.
This paper introduced a stochastic disturbance and an attractive operator into the standard particle swarm optimization (SPSO) algorithm to improve its performance in a predefined number of generations. It termed as stochastic disturbance particle swarm optimization based on attractive operator (SDPSO). In this paper, the concept of attractive operator is recommended that every particle has its own...
Aiming at the premature convergence problem of particle swarm optimization algorithm, a new particle swarm Optimization algorithm with dynamic adaptive inertia weigh was presented to solve the typical multi-peak, high dimensional function optimization problems. The dynamic adaptive strategy was introduced in this new algorithm and the change of inertia weight was formulated as an adjust function of...
One of the primary complaints toward particle swarm optimization (PSO) is the occurrence of premature convergence because the diversity of the particles rapidly comedown. In order to improve diversity of the particles, a dynamical particle swarm optimization (DPSO) is proposed for global optimization, which adds a memory mechanism conceptually derived from the principle free entropy minimization....
In order to increase the accuracy of the cost estimates in government investment, a method based on the PSO trained neural network to estimate the cost is proposed. First the neural network model of a project cost estimate is created, and then PSO is introduced to optimize the weight and threshold of the neural network, at last the neural network trained is used to estimate cost of the project. The...
Neural network has been widely used in the field of data mining, but the traditional neural network has some defects, such as convergence in the local optimal solution, learning a long time, etc. The genetic algorithm is a global optimization search algorithm, and can effectively overcome these shortcomings. Therefore, based on the comparative analysis of the standard BP algorithm and genetic algorithms,...
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.