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 Authors are invited to submit their original and unpublished work related to swarm intelligence, including research, theory, development, and applications.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 ...
Ozcan, E.; Mohan, C.K. Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on, 1999
A new optimization method has been proposed by J. Kennedy and R.C. Eberhart (1997; 1995), called Particle Swarm Optimization (PSO). This approach combines social psychology principles and evolutionary computation. It has been applied successfully to nonlinear function optimization and neural network training. Preliminary formal analyses showed that a particle in a simple one-dimensional PSO system follows a path defined by ...
Kennedy, J. Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on, 1999
The study manipulated the neighborhood topologies of particle swarms optimizing four test functions. Several social network structures were tested, with "small-world" randomization of a specified number of links. Sociometric structure and the small-world manipulation interacted with function to produce a significant effect on performance
Xing-wei Wang; Pei-yu Qin; Min Huang; Hui Cheng Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on, 2009
In this paper, a QoS handoff decision scheme with ABC (always best connected) supported is proposed, and an optimal handoff solution of assigning N terminals to M access networks is found based on niche PSO algorithm. With help of gaming analysis, Pareto optimum under Nash equilibrium of user utility and network provider utility is achieved or approached for the found ...
Zabidi, A.; Mansor, W.; Lee Yoot Khuan; Yassin, I.M.; Sahak, R. Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on, 2010
This paper describes the optimization of Mel Frequency Cepstral Coefficients (MFCC) parameters using Discrete Mutative Particle Swarm Optimization (DMPSO) for diagnosis of hypothyroidism in infants. The MFCC was used to extract the feature set from infant cry signals. The features were then classified using Multi-Layer Perceptron (MLP). The DMPSO variants optimize the number of filter banks and number of cepstral ...
Maoguo Gong; Licheng Jiao; Licheng Jiao; Chao Liu Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on, 2009
In this study, a novel clustering-based selection strategy of nondominated individuals for evolutionary multi-objective optimization is proposed. The new strategy partitions the nondominated individuals in current Pareto front adaptively into desired clusters. Then one representative individual will be selected in each cluster for pruning nondominated individuals. In order to evaluate the validity of the new strategy, we apply it into ...
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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