1,721,213 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Distributed Niching Concept for Electromagnetic Shape Optimization by Genetic Algorithm

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    Genetic Algorithms are becoming a common tool for optimal design applications, where, due to the multiple solutions issue, global search techniques are required. Anyway, when dealing with real problems, involving several degrees of freedom, the actual computing power restricts the global search ability. The availability of cheap hardware has recently caused the spreading of multiprocessors computing systems. In particular, new genetic techniques have been proposed to adapt the method’s characteristics to the parallel architecture, allowing in this way also to deal with real problems. One of these techniques, called niching approach, can be implemented by dividing the population into subgroups, and letting each group to evolve on one of the processors, interacting only when scheduled. Objective of this work is to discuss the perspectives of niching approaches in the electromagnetic optimal design applications. As an example case, preliminary results about SMES (Superconducting Magnetic Energy Storage) devices are proposed

    Increasing design robustness in evolutionary optimisation

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    The role of the parameters uncertainness in the optimal design of electromagnetic devices is discussed and an efficient strategy to look for robustness of feasible solutions is proposed. A suitable modification of the objective function (OF) is used to rank different device configurations on the basis of their ability to maintain the required performances against small parameters modifications due to construction tolerances. In the frame of a genetic algorithm approach, the modified OF has been able to address the evolutionary optimisation towards more robust solutions
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