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Titlebook: Bio-inspired Computing – Theories and Applications; 11th International C Maoguo Gong,Linqiang Pan,Gexiang Zhang Conference proceedings 2016

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楼主: 誓约
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https://doi.org/10.1007/978-981-10-3614-9Bio-inspired computing; Neural computing; Evolutionary computation; Membrane computing; DNA computing; Mu
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Bio-inspired Computing – Theories and Applications978-981-10-3614-9Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Kernel Evolutionary Algorithm for Clusteringce based similarity metrics can help clustering algorithms handle datasets with compact super-sphere distributions perfectly, but it is undesirable for the complex structural or irregular shaped datesets. Proper mapping function can map the data in original space to high-dimensional feature space, w
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Unsupervised Image Segmentation Based on Watershed and Kernel Evolutionary Clustering Algorithmatershed algorithm, marker driven watershed transform, is used to segment image into many small regions and the image features of every region are extracted. By using kernel functions, the image features in the original space are mapped to a high-dimensional feature space, in which we can perform cl
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Overlapping Community Detection in Network: A Fuzzy Evaluation Approachrk also overlap as a person may belong to more than one social group. Therefore, detecting overlapping partition of a network is necessary for the realistic social analysis. In this paper, We develop a fuzzy evaluation using the membership degree of each node belonging to every community, and presen
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