Particle swarm optimization
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2014 IEEE Congress on Evolutionary Computation (CEC)
IEEE Congress on Evolutionary Computation is the largest technical event in the field of evolutionary computation. In 2014, International Joint Conference on Neural Networks will be part of the 2104 IEEE World Congress on Computational Intelligence.
2014 IEEE World Congress on Computational Intelligence (WCCI)
IEEE World Congress on Computational Intelligence (IEEE WCCI) is the largest technical event in the field of computational intelligence. IEEE WCCI 2014 will host three conferences: The 2014 International Joint Conference on Neural Networks, the 2014 IEEE International Conference on Fuzzy Systems, and the 2014 IEEE Congress on Evolutionary Computation.
2013 25th Chinese Control and Decision Conference (CCDC)
Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.
2013 9th International Conference on Natural Computation (ICNC)
ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, biomedical engineering, computers, circuits, systems, control, communications, and more.
2013 IEEE Symposium on Swarm Intelligence (SIS)
It will be part of the IEEE Symposium Series on Computational Intelligence 2013, which consists of over 20 symposia. The theme of the SIS2013 is to provide a platform for researchers, academicians, students, engineers, and government officers from all over the world to share and exchange information in the swarm intelligence research areas ranging from algorithm development to real-world applications. Authors are invited to submit their original and unpublished work related to swarm intelligence, including
Xinghua Wu Electrical and Control Engineering (ICECE), 2011 International Conference on, 2011
In this paper, a density adjustment based Particle swarm optimization algorithm is proposed to solve the problem of premature convergence and global optimal in traditional Particle swarm optimization algorithm. Measure the density of particle swarm by entropy, and update the particle swarm to maintain the swarm diversity, which can also help to improve the ability of global optimization. At the ...
Fengrui Zhang; Jianshu Cao; Zhenhui Xu Communications, Circuits and Systems (ICCCAS), 2013 International Conference on, 2013
To solve the problem in Particle Swarm Optimization Particle Filtering algorithm that it can be premature too easy to fall into local minima search results, this paper proposes the Particle Swarm Optimization based Fission Bootstrap Particle Filter algorithm. The algorithm first search the space for the particle set by Particle Swarm Optimization, it makes the particle set move to a ...
Yan Zhe-ping; Deng Chao; Zhou Jia-jia; Chi Dong-nan Intelligent Control and Automation (WCICA), 2012 10th World Congress on, 2012
The performance of the particle swarm is mainly influenced by individual particles experience and group experience in the period of evolution for particle swarm optimization. To make full use of the two factors and effectively improve the particle swarm optimization performance, Introduced a novel Two-subpopulation Particle Swarm Optimization, The proportion of individual experience and group experiences is different in each ...
Yangguang Fu; Mingyue Ding; Chengping Zhou Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 2012
A new variant of particle swarm optimization (PSO), named phase angle-encoded and quantum-behaved particle swarm optimization (θ-QPSO), is proposed. Six versions of θ-QPSO using different mappings are presented and compared through their application to solve continuous function optimization problems. Several representative benchmark functions are selected as testing functions. The real-valued genetic algorithm (GA), differential evolution (DE), standard particle swarm optimization ...
Anantathanavit, M.; Munlin, M.-A. Computer Science and Engineering Conference (ICSEC), 2013 International, 2013
Particle Swarm Optimization (PSO) is a swarm intelligence based and stochastic algorithm to solve the optimization problem. Nevertheless, the traditional PSO has disadvantage from the premature convergence when finding the global optimization. To prevent from falling into the local optimum, we propose the Radius particle swarm optimization (R-PSO) which extends the Particle Swarm Optimization by regrouping the agent particles within ...
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Rahmat-Samii, Yahya Evolutionary Optimization Methods for Engineering: Part II - Particle Swarm Optimization, 2011
Optimization is the process of upgrading something to perform better. Engineers constantly look for improving their designs in multi parametric solution space. Imagine that you will be able to use nature.s evolutionary processes to obtain the best parameters for your designs. This is the subject of this course which is divided into two parts. This course is Part II and ...
Rahmat-Samii, Yahya Evolutionary Optimization Methods for Engineering: Part I - Genetic Algorithms, 2011
Optimization is the process of upgrading something to perform better. Engineers constantly look for improving their designs in multi parametric solution space. Imagine that you will be able to use nature's evolutionary processes to obtain the best parameters for your designs. This is the subject of this course which is divided into two parts. This course is Part I and ...
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