Particle swarm optimization

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In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. (Wikipedia.org)






Conferences related to 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.

  • 2013 IEEE Congress on Evolutionary Computation (CEC)

    CEC 2013 will bring together researchers and practitioners in the field of evolutionary computation and computational intelligence from around the globe. Theory, applications, algorithmic developments and all other aspects of evolutionary computation and related areas (i.e., any other bio-inspired metaheuristics) are welcome to contribute to this conference.

  • 2012 IEEE Congress on Evolutionary Computation (CEC)

    The annual IEEE CEC is one of the leading events in the field of evolutionary computation.

  • 2011 IEEE Congress on Evolutionary Computation (CEC)

    Annual Congress on Evolutionary Computation.


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 Authors are invited to submit their original and unpublished work related to swarm intelligence, including research, theory, development, and applications.


2012 24th 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.


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.

  • 2011 4th International Conference on Intelligent Networks and Intelligent Systems (ICINIS)

    The 4th International Conference on Intelligent Networks and Intelligent Systems (ICINIS 2011) aims to provide a high-level 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.

  • 2010 3rd International Conference on Intelligent Networks and Intelligent Systems (ICINIS)

    The Field of Interest of the Society shall be the theory, design, application, and develo pment of intelligent computer networks an d systems using biologically inspired co mputational paradigms such as neural net works, evolutionary algorithms and fuzzy sets.

  • 2009 Second International Conference on Intelligent Networks and Intelligent Systems (ICINIS)

    The INASS, a non-profit organization, is the professional association for the advancement of intelligent technology. The INASS devotes to promote the engineering process of creating, developing, integrating, sharing, and applying knowledge about intelligent science and information technologies for the benefit of humanity and the profession . About 30% of the accepted papers of this conference will be selected for possible publication in the special issue of the International Journal of Intelligent Engineeri


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Periodicals related to Particle swarm optimization

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Evolutionary Computation, IEEE Transactions on

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, Man and Cybernetics, Part A, IEEE Transactions on

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. ...


Systems, Man, and Cybernetics, Part B, IEEE Transactions on

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, ...


Transactions on Sustainable Energy

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 ...




Xplore Articles related to Particle swarm optimization

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Engine performance simulation using improved PSO algorithm

Yonghua Wang; Feixiang Zhu Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on, 2012

Turbo fan engine mathematical model is a highly complex nonlinear system. Solving engine mathematical model with traditional iteration methods turns out to be difficult as these methods are very sensitive to initial values. Therefore particle swarm optimization is used to solve the model. An improved particle swarm optimization algorithm is produced. The mechanism of immune is introduced in the new ...


Type 2 fuzzy adaptive binary particle swarm optimization for optimal placement and sizing of distributed generation

Soeprijanto, A.; Abdillah, M. Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME), 2011 2nd International Conference on, 2011

This paper proposes a new method for optimizing the placement and size of distributed generation (DG) using type-2 fuzzy adaptive binary particle swarm optimization with single mutation operator, called T2FABPSOM. The objective function of the proposed method to minimize active power losses in transmission line with the bus voltage system constraints is allowed. Type-2 fuzzy logic system (type-2 FLS) is ...


Study of Strip Flatness and Gauge Complex Control Based on Improved PSO-RBF Neural Networks

Lin Xu; Xiaoke Fang; Qichao Fang; Jianhui Wang; Shusheng Gu Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on, 2006

An improved particle swarm optimization (IPSO) is presented to solve the premature and low precision based on shrinking chaotic mutation with population's fitness, which is used to train the radius basis function (RBF) neural networks, and optimization parameters of the network. Considering the stronger nonlinearity and coupling of strip flatness and gauge complex control, using the IPSO-RBF neural networks as ...


Energy balancing multiple sink optimal deployment in multi-hop Wireless Sensor Networks

Dandekar, D.R.; Deshmukh, P.R. Advance Computing Conference (IACC), 2013 IEEE 3rd International, 2013

In a multi-hop WSN a sensor node spends most of its energy for relaying data packets due to which energy reduction is one of the major issue in the designing of a wireless sensor network to prolong the lifetime of a network. One of the solutions of this problem is to shorten the hop distance a sensor's data that has ...


Analysis of the Superiority of Parameter Optimization over Genetic Programming for a Difficult Object Detection Problem

Ciesielski, V.; Wijesinghe, G.; Innes, A.; John, S. Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, 2006

We describe a progression of solutions to a di ffi cult object detection problem, that of locating landmarks in X-Rays used in orthodontic treatment planning. In our fi rst formula tion an object detector was a genetic program whose inputs were a number of attributes computed from a scanning window. We used a rich function set comprising f+; ; -; ...


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Engine performance simulation using improved PSO algorithm

Yonghua Wang; Feixiang Zhu Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on, 2012

Turbo fan engine mathematical model is a highly complex nonlinear system. Solving engine mathematical model with traditional iteration methods turns out to be difficult as these methods are very sensitive to initial values. Therefore particle swarm optimization is used to solve the model. An improved particle swarm optimization algorithm is produced. The mechanism of immune is introduced in the new ...


Type 2 fuzzy adaptive binary particle swarm optimization for optimal placement and sizing of distributed generation

Soeprijanto, A.; Abdillah, M. Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME), 2011 2nd International Conference on, 2011

This paper proposes a new method for optimizing the placement and size of distributed generation (DG) using type-2 fuzzy adaptive binary particle swarm optimization with single mutation operator, called T2FABPSOM. The objective function of the proposed method to minimize active power losses in transmission line with the bus voltage system constraints is allowed. Type-2 fuzzy logic system (type-2 FLS) is ...


Study of Strip Flatness and Gauge Complex Control Based on Improved PSO-RBF Neural Networks

Lin Xu; Xiaoke Fang; Qichao Fang; Jianhui Wang; Shusheng Gu Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on, 2006

An improved particle swarm optimization (IPSO) is presented to solve the premature and low precision based on shrinking chaotic mutation with population's fitness, which is used to train the radius basis function (RBF) neural networks, and optimization parameters of the network. Considering the stronger nonlinearity and coupling of strip flatness and gauge complex control, using the IPSO-RBF neural networks as ...


Energy balancing multiple sink optimal deployment in multi-hop Wireless Sensor Networks

Dandekar, D.R.; Deshmukh, P.R. Advance Computing Conference (IACC), 2013 IEEE 3rd International, 2013

In a multi-hop WSN a sensor node spends most of its energy for relaying data packets due to which energy reduction is one of the major issue in the designing of a wireless sensor network to prolong the lifetime of a network. One of the solutions of this problem is to shorten the hop distance a sensor's data that has ...


Analysis of the Superiority of Parameter Optimization over Genetic Programming for a Difficult Object Detection Problem

Ciesielski, V.; Wijesinghe, G.; Innes, A.; John, S. Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, 2006

We describe a progression of solutions to a di ffi cult object detection problem, that of locating landmarks in X-Rays used in orthodontic treatment planning. In our fi rst formula tion an object detector was a genetic program whose inputs were a number of attributes computed from a scanning window. We used a rich function set comprising f+; ; -; ...


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