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 Authors are invited to submit their original and unpublished work related to swarm intelligence, including research, theory, development, and applications.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 ...
Huang, T.; Mohan, A.S. Antennas and Propagation Society International Symposium, 2005 IEEE, 2005
In this paper we have attempted to solve this inverse scattering problem by a global optimization procedure known as the particle swarm optimization (PSO) technique. The PSO technique is a stochastic optimization technique first introduced by Eberhart and Kennedy and was recently introduced to the antenna community by Robinson and Rahmat-Samii. The technique is based on the social interaction of ...
Shanhe Jiang; Yusheng Chen; Julang Jiang; Qishen Wang Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on, 2008
Satisfactory results have been acquired in functional optimization by adopting particle swarm optimization. Its significant feature is simpler expression, less parameters and easier operation. However, selection of key parameters has great influence on algorithm effects. The enactment of the parameters of particle swarm optimization has been determined by experience and experiment. This leads to heavy work and makes the optimal ...
Tuan Anh To; Dang Anh Tuan; Vo Chi Thanh; Siddiqi, U.F.; Shiraishi, Y.; Motegi, K. Electrical Design of Advanced Packaging and Systems Symposium (EDAPS), 2013 IEEE, 2013
This paper deals with a component placement algorithm for 3D IC design. The Particle Swarm Optimization (PSO) is a general purpose stochastic algorithm mimicking the behaviors of particles self-organizing a system. The size of solution space is very large in the 3D component placement problem and it is afraid that the objective function value will be degraded. The Clustering Algorithm ...
Ho, I.S.F.; Safaai, D.; Zaiton, M. Computer Engineering and Technology, 2009. ICCET '09. International Conference on, 2009
The university course timetabling problem is a combinatorial optimization problem concerning the scheduling of a number of subjects into a finite number of timeslots in order to satisfy a set of specified constraints. The timetable problem can be very hard to solve, especially when attempting to find a near- optimal solutions, with a large number of instances. This paper presents ...
Helbig, M.; Engelbrecht, A.P. Evolutionary Computation (CEC), 2012 IEEE Congress on, 2012
The vector evaluated particle swarm optimisation (VEPSO) algorithm is a multi- swarm variation of particle swarm optimisation (PSO) used to solve static multi-objective optimisation problems (SMOOPs). Recently, VEPSO was extended to the dynamic VEPSO (DVEPSO) algorithm to solve dynamic multi-objective optimisation problems (DMOOPs) that have at least one objective that changes over time. The search process of DVEPSO is driven ...
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