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Computational Intelligence Magazine, IEEE

Issue 2 • Date May 2010

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Displaying Results 1 - 25 of 27
  • [Front cover]

    Publication Year: 2010 , Page(s): C1
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  • IEEE Proceedings [advertisement]

    Publication Year: 2010 , Page(s): C2
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  • Table of contents

    Publication Year: 2010 , Page(s): 1
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  • Not Just a “Meme” to an End [Editor's Remarks]

    Publication Year: 2010 , Page(s): 2 - 14
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  • Call for Volunteers–Part 1 [President's Message]

    Publication Year: 2010 , Page(s): 3 - 4
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  • Correction

    Publication Year: 2010 , Page(s): 4
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  • IEEE Learning [advertisement]

    Publication Year: 2010 , Page(s): 5
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  • IEEE CIS VP-Technical Activities Vision Statement [Society Briefs]

    Publication Year: 2010 , Page(s): 6
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  • Newly Elected CIS Administrative Committee Members (2010–2012) [Society Briefs]

    Publication Year: 2010 , Page(s): 7 - 9
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  • IEEE Fellows—Class of 2010 [Society Briefs]

    Publication Year: 2010 , Page(s): 9 - 12
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  • CIS Publication Spotlight [Publication Spotlight]

    Publication Year: 2010 , Page(s): 13 - 14
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  • Information for Authors

    Publication Year: 2010 , Page(s): 15
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  • United Kingdom and Republic of Ireland Chapter Report [Family Corner]

    Publication Year: 2010 , Page(s): 16 - 19
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  • IEEE CIG 2009 Conference Report [Conference Report]

    Publication Year: 2010 , Page(s): 20 - 22
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  • ECP [Educational Control Products - advertisement]

    Publication Year: 2010 , Page(s): 23
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  • Memetic Computation—Past, Present & Future [Research Frontier]

    Publication Year: 2010 , Page(s): 24 - 31
    Cited by:  Papers (50)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3185 KB) |  | HTML iconHTML  

    Taking a lead from the multi-faceted definitions and roles of the term "meme" in memetics, a plethora of potentially rich memetic computing methodologies, frameworks and operational memeinspired algorithms have been developed with considerable success in several realworld domains in the last two decades. This article showcase several successful deployments of memetic computing methodologies for so... View full abstract»

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  • Memetic Mission Management [Application Notes]

    Publication Year: 2010 , Page(s): 32 - 40
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1735 KB) |  | HTML iconHTML  

    This paper presents novel area coverage algorithms that have been validated using Boeing VSTL hardware. Even though the multi-vehicle search area coverage problem is large and complex, several new memetic computing methods have been presented that decompose, allocate and optimize the exploration of a search area for multiple heterogeneous vehicles. These new methods were shown to have good perform... View full abstract»

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  • Towards a Memetic Feature Selection Paradigm [Application Notes]

    Publication Year: 2010 , Page(s): 41 - 53
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2302 KB) |  | HTML iconHTML  

    Feature selection has become the focus of many real-world application oriented developments and applied research in recent years. With the rapid advancement of computer and database technologies, problems "with hundreds and thousands of variables or features are now ubiquitous in pattern recognition, data mining, and machine learning [1], [2]. In this article, we consider two real-world feature se... View full abstract»

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  • Memetic Compact Differential Evolution for Cartesian Robot Control

    Publication Year: 2010 , Page(s): 54 - 65
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2402 KB) |  | HTML iconHTML  

    This article deals with optimization problems to be solved in the absence of a full power computer device. The goal is to solve a complex optimization problem by using a control card related to portable devices, e.g. for the control of commercial robots. In order to handle this class of optimization problems, a novel Memetic Computing approach is presented. The proposed algorithm employs a Differe... View full abstract»

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  • Exploring e-Learning Knowledge Through Ontological Memetic Agents

    Publication Year: 2010 , Page(s): 66 - 77
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3048 KB) |  | HTML iconHTML  

    E-Learning systems have proven to be fundamental in several areas of tertiary education and in business companies. There are many significant advantages for people who learn online such as convenience, portability, flexibility and costs. However, the remarkable velocity and volatility of modern knowledge due to the exponential growth of the World Wide Web, requires novel learning methods that offe... View full abstract»

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  • Natural and Remote Sensing Image Segmentation Using Memetic Computing

    Publication Year: 2010 , Page(s): 78 - 91
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (11474 KB) |  | HTML iconHTML  

    In order to solve the image segmentation problem which assigns a label to every pixel in an image such that pixels with the same label share certain visual characteristics more effectively, a novel approach based on memetic algorithm (MISA) is proposed. Watershed segmentation is applied to segment original images into non-overlap small regions before performing the portioning process by MISA. MISA... View full abstract»

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  • Hybrid Approaches and Dimensionality Reduction for Portfolio Selection with Cardinality Constraints

    Publication Year: 2010 , Page(s): 92 - 107
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (4786 KB) |  | HTML iconHTML  

    A novel memetic algorithm that combines evolutionary algorithms, quadratic programming, and specially devised pruning heuristics is proposed for the selection of cardinality-constrained optimal portfolios. The framework used is the standard Markowitz mean-variance formulation for portfolio optimization with constraints of practical interest, such as minimum and maximum investments per asset and/or... View full abstract»

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  • Applying Computational Intelligence: How to Create Value (Kordon, A.K.; 2010) [Book Review]

    Publication Year: 2010 , Page(s): 108 - 109
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  • Conference Calendar

    Publication Year: 2010 , Page(s): 110 - 111
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  • Advertisers index

    Publication Year: 2010 , Page(s): 112
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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). 

Full Aims & Scope