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 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 Authors are invited to submit their original and unpublished work related to swarm intelligence, including research, theory, development, and applications.
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.
2012 5th International Conference on Intelligent Networks and Intelligent Systems (ICINIS)
The 5th International Conference on Intelligent Networks and Intelligent Systems (ICINIS 2012) aims to provide an international forum for scientists, engineers, and educators to present the state of the art of intelligent networks and systems research and applications in various disciplines.
Papers on application, design, and theory of evolutionary computation, with emphasis given to engineering systems and scientific applications. Evolutionary optimization, machine learning, intelligent systems design, image processing and machine vision, pattern recognition, evolutionary neurocomputing, evolutionary fuzzy systems, applications in biomedicine and biochemistry, robotics and control, mathematical modelling, civil, chemical, aeronautical, and industrial engineering applications.
Systems engineering, including efforts that involve issue formnaulations, issue analysis and modeling, and decision making and issue interpretation at any of the life-cycle phases associated with the definition, development, and implementation of large systems. It will also include efforts that relate to systems management, systems engineering processes and a variety of systems engineering methods such as optimization, modeling and simulation. ...
The scope of the IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or between machines, humans, and organizations. The scope of Part B includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, ...
The IEEE Transactions on Sustainable Energy is a cross disciplinary and internationally archival journal aimed at disseminating results of research on sustainable energy that relates to, arises from, or deliberately influences energy generation, transmission, distribution and delivery. The journal will publish original research on theories and development on principles of sustainable energy technologies and systems.This journal will cover the following ...
Derr, K.; Manic, M. Human System Interactions, 2009. HSI '09. 2nd Conference on, 2009
Multiple small robots (swarms) can work together using particle swarm optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of ...
Youngmin Ha Machine Learning and Applications (ICMLA), 2012 11th International Conference on, 2012
A new mesh-based algorithm to solve partial differential equations (PDEs) using quantum-behaved particle swarm optimization (QPSO) with random Gaussian function and random median filter is proposed in this paper. The random Gaussian function behaves as a mutation operator of QPSO to escape from local minima, and the random median filter accelerates the convergence of QPSO. It provides accurate results for ...
Al-Hinai, A.; Feliachi, A. Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE, 2008
A new approach based on particle swarm optimization technique is proposed for the design of load following controller for microturbines in a competitive distributed generation power system. The objective is to avoid any power change from upper system when there is small load change in the local distribution system. A case study for IEEE-37 Node Feeder is presented to illustrate ...
Tukel, Y.; Bozbey, A.; Tunc, C.A. Applied Superconductivity, IEEE Transactions on, 2013
Successful fabrication and demonstration of complex Rapid Single Flux Quantum (RSFQ) circuits depend heavily on the reliability of the cell library that is used for the design. In large-scale RSFQ integrated circuits, delay fluctuations (jitter) of each cell may occur due to fabrication tolerances. The fabrication-induced jitter of each cell might accumulate at each stage and bring out larger variations ...
Galan, A.Y.; Boryskina, O.P.; Sauleau, R.; Boriskin, A.V. Antennas and Propagation (EUCAP), Proceedings of the 5th European Conference on, 2011
An advanced modification of the particle swarm optimization (PSO) algorithm is presented. The proposed modification consists in implementation of floating boundaries for the design space whose positions are moved (shrink or expand) during computations depending on the number of particle hits. As demonstrated by example of three test functions, such an adaptive "moving boundary PSO" algorithm outperforms its classical analog ...
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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