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IEEE Computational Intelligence Magazine

Issue 1 • Feb. 2016

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Displaying Results 1 - 23 of 23
  • Front Cover

    Publication Year: 2016, Page(s): C1
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  • IEEE WCCI 2016

    Publication Year: 2016, Page(s): C2
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  • Table of Contents

    Publication Year: 2016, Page(s): 1
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  • CIM Editorial Board

    Publication Year: 2016, Page(s): 2
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  • Second Term as Editor-in-Chief [Editor's Remarks]

    Publication Year: 2016, Page(s): 2
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  • CIS in the Next Decade [President's Message]

    Publication Year: 2016, Page(s):3 - 53
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  • CIS Society Officers

    Publication Year: 2016, Page(s): 3
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  • 2016 IEEE CIS Awards [Society Briefs]

    Publication Year: 2016, Page(s):4 - 7
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  • Conference Report on 2015 International Joint Conference on Neural Networks (IJCNN 2015) [Conference Reports]

    Publication Year: 2016, Page(s):8 - 10
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  • Conference Report on 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015) [Conference Reports]

    Publication Year: 2016, Page(s):11 - 13
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  • Conference Report on 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2015) [Conference Reports]

    Publication Year: 2016, Page(s):13 - 14
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  • CIS Publication Spotlight [Publication Spotlight]

    Publication Year: 2016, Page(s):15 - 17
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  • Call for Papers for Journal Special Issues

    Publication Year: 2016, Page(s): 17
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  • Computational Intelligence for Brain Computer Interface [Guest Editorial]

    Publication Year: 2016, Page(s): 18
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  • 2017 Congress on Evolutionary Computation

    Publication Year: 2016, Page(s): 19
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  • Transfer Learning in Brain-Computer Interfaces

    Publication Year: 2016, Page(s):20 - 31
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2443 KB) | HTML iconHTML

    The performance of brain-computer interfaces (BCIs) improves with the amount of available training data; the statistical distribution of this data, however, varies across subjects as well as across sessions within individual subjects, limiting the transferability of training data or trained models between them. In this article, we review current transfer learning techniques in BCIs that exploit sh... View full abstract»

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  • Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

    Publication Year: 2016, Page(s):32 - 39
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2455 KB) | HTML iconHTML

    One of the challenges of using brain-computer interfaces (BCIs) over extended periods of time is the variation of the users' performance from one experimental day to another. The goal of the current study is to propose a performance estimator for an electroencephalography-based motor imagery BCI by assessing the reliability of a command (i.e., predicting a 'short' or 'long' command delivery time, ... View full abstract»

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  • FUZZ-IEEE 2017

    Publication Year: 2016, Page(s): 40
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  • Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]

    Publication Year: 2016, Page(s):41 - 53
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (773 KB) | HTML iconHTML

    Ensemble methods use multiple models to get better performance. Ensemble methods have been used in multiple research fields such as computational intelligence, statistics and machine learning. This paper reviews traditional as well as state-of-the-art ensemble methods and thus can serve as an extensive summary for practitioners and beginners. The ensemble methods are categorized into conventional ... View full abstract»

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  • 2016 IEEE Symposium Series on Computational Intelligence

    Publication Year: 2016, Page(s): 54
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  • Evolutionary Fleet Sizing in Static and Uncertain Environments with Shuttle Transportation Tasks-The Case Studies of Container Terminals [Application Notes]

    Publication Year: 2016, Page(s):55 - 69
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3680 KB) | HTML iconHTML

    This paper aims to identify the optimal number of vehicles in environments with shuttle transportation tasks. These environments are very common industrial settings where goods are transferred repeatedly between multiple machines by a fleet of vehicles. Typical examples of such environments are manufacturing factories, warehouses and container ports. One very important optimization problem in thes... View full abstract»

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  • IEEE WCCI 2018

    Publication Year: 2016, Page(s): 70
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  • [Conference Calendar]

    Publication Year: 2016, Page(s): 71
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Aims & Scope

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications, in keeping with the Field of Interest of the IEEE Computational Intelligence Society (IEEE/CIS).

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