By De-Shuang Huang, Vitoantonio Bevilacqua, Prashan Premaratne
This two-volume set LNCS 9225 and LNCS 9226 constitutes - along with the amount LNAI 9227 - the refereed complaints of the eleventh foreign convention on clever Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The 191 complete papers and forty two brief papers of this quantity have been rigorously reviewed and chosen from 191 submissions. The papers are geared up in topical sections resembling evolutionary computation and studying; compressed sensing, sparse coding and social computing; neural networks, nature encouraged computing and optimization; trend attractiveness and sign processing; snapshot processing; biomedical informatics concept and strategies; differential evolution, particle swarm optimization and area of interest expertise; clever computing and data discovery and information mining; gentle computing and desktop studying; computational biology, protein constitution and serve as prediction; genetic algorithms; man made bee colony algorithms; swarm intelligence and optimization; social computing; details safeguard; digital truth and human-computer interplay; healthcare informatics conception and strategies; unsupervised studying; collective intelligence; clever computing in robotics; clever computing in communique networks; clever keep an eye on and automation; clever information research and prediction; gene expression array research; gene rules modeling and research; protein-protein interplay prediction; biology encouraged computing and optimization; research and visualization of enormous organic info units; motif detection; biomarker discovery; modeling; simulation; and optimization of organic platforms; biomedical facts modeling and mining; clever computing in biomedical signal/image research; clever computing in mind imaging; neuroinformatics; cheminformatics; clever computing in computational biology; computational genomics; exact consultation on biomedical facts integration and mining within the period of massive facts; targeted consultation on mammoth facts analytics; specific consultation on synthetic intelligence for ambient assisted dwelling; and specified consultation on swarm intelligence with discrete dynamics.
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Extra resources for Intelligent Computing Theories and Methodologies: 11th International Conference, ICIC 2015, Fuzhou, China, August 20-23, 2015, Proceedings, Part I
Cluster analysis of multivariate data: efﬁciency versus interpretability of classiﬁcations.
As can be seen from Table 1, the proposed algorithm for C class problems can always get the optimal results or better results, while for R and RC class problems there exists certain bias to the optimal solution, mainly due to the design of the proposed algorithm is a macro-design based on our thoughts of the algorithm, while the speciﬁc design details such as initialization method, local search methods haven’t yet been in detailed design, in addition, all of the running time of the proposed algorithm is limited in 50 s, while in  the algorithm running time are typically between 2−7 h.
23–33, 2015. 1007/978-3-319-22180-9_3 24 L. Gong et al. been proposed to obtain the initial values of the factorization variables in a more sophisticated way, in order to improve the rate of convergence. For example, spherical k-means clustering is used to initialize one factorization matrix, and then nonnegative least square is used to derive the other factorization matrix . Principal component analysis (PCA) can also be used to perform such initialization, for which non-negativity of the factorization variables can be enforced by either converting all the negative elements of the PCA output to zero  or keeping the absolute values .