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IEEE Computational Intelligence Magazine

Issue 3 • Aug. 2011

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Displaying Results 1 - 19 of 19
  • [Front cover]

    Publication Year: 2011, Page(s): C1
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  • 2012 IEEE World Congress on Computational Intelligence

    Publication Year: 2011, Page(s): C2
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  • [Table of Contents]

    Publication Year: 2011, Page(s): 1
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  • Nothing's Too Small to Have an Impact [Editor's Remarks]

    Publication Year: 2011, Page(s): 2
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  • Global Outreach [President's Message]

    Publication Year: 2011, Page(s):3 - 11
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  • IEEE CIS Webinars Activities and Future Plan [Society Briefs]

    Publication Year: 2011, Page(s):4 - 5
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  • What it Means to Be a Young CI Researcher in the 21st Century [Society Briefs]

    Publication Year: 2011, Page(s):6 - 7
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  • IEEE Computational Intelligence Society Winter School 2011 [Society Briefs]

    Publication Year: 2011, Page(s): 8
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  • In Memoriam: Dr. Herbert E. Rauch October 6, 1935–March 29, 2011 [Obituary]

    Publication Year: 2011, Page(s):9 - 59
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  • CIS Publication Spotlight [Publication Spotlight]

    Publication Year: 2011, Page(s):10 - 11
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  • Special Issue on Computational Intelligence in Smart Grid [Guest Editorial]

    Publication Year: 2011, Page(s):12 - 64
    Cited by:  Papers (17)
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  • IEEE Transactions on Computational Intelligence and Al in Games

    Publication Year: 2011, Page(s): 13
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  • Computational Intelligence for the Smart Grid-History, Challenges, and Opportunities

    Publication Year: 2011, Page(s):14 - 21
    Cited by:  Papers (39)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1637 KB) | HTML iconHTML

    This paper reviews the evolution of four generations of concepts of the “smart grid,” the role of computational intelligence in meeting their needs, and key examples of relevant research and tools. The first generation focused on traditional concepts like building more wires, automated meters, workforce development, and reducing blackouts, but it already had many uses for computation... View full abstract»

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  • Dynamic, Stochastic, Computational, and Scalable Technologies for Smart Grids

    Publication Year: 2011, Page(s):22 - 35
    Cited by:  Papers (61)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2791 KB) | HTML iconHTML

    The smart electric power grid will evolve into a very complex adaptive system under semi-autonomous distributed control. Its spatial and temporal complexity, non-convexity, non-linearity, non-stationarity, variability and uncertainties exceed the characteristics found in today's traditional power system. The distributed integration of intermittent sources of energy and plug-in electric vehicles to... View full abstract»

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  • A Belief Propagation Based Power Distribution System State Estimator

    Publication Year: 2011, Page(s):36 - 46
    Cited by:  Papers (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2123 KB) | HTML iconHTML

    The most popular method used in traditional power system state estimation is the Maximum Likelihood Estimation (MLE). It assumes the state of the system is a set of deterministic variables and determines the most likely state via error included interval measurements. In the distribution system, the measurements are often too sparse to fulfill the system observability. Instead of introducing pseudo... View full abstract»

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  • Short-Term Load Forecasting with Neural Network Ensembles: A Comparative Study [Application Notes]

    Publication Year: 2011, Page(s):47 - 56
    Cited by:  Papers (42)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (853 KB) | HTML iconHTML

    Load Forecasting plays a critical role in the management, scheduling and dispatching operations in power systems, and it concerns the prediction of energy demand in different time spans. In future electric grids, to achieve a greater control and flexibility than in actual electric grids, a reliable forecasting of load demand could help to avoid dispatch problems given by unexpected loads, and give... View full abstract»

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  • Experience of Teaching Computational Intelligence in an Undergraduate Level Course [Educational Forum]

    Publication Year: 2011, Page(s):57 - 59
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  • Information Theoretic Learning: Reny's Entropy and Kernel Perspectives (Principe, J.; 2010) [Book Review]

    Publication Year: 2011, Page(s):60 - 62
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  • [Conference Calendar]

    Publication Year: 2011, Page(s):63 - 64
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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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