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Titlebook: High Performance Computing in Science and Engineering, Garching/Munich 2009; Transactions of the Siegfried Wagner,Matthias Steinmetz,Marku

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Ch. Gobert,M. Manhart This chapter presents a comparative study related to the prediction of cancer cells based on Machine Learning and Evolutionary Algorithms. As well as, a brief introduction of machine learning and evolutionary technics is presented. Also, the procedures’ implementation and performance are described.
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metric to be holomorphic; also, we prove that there exists a one-to-one correspondence between hypercomplex anti-Kähler manifolds and anti-Hermitian manifolds with an .-holomorphic metrics. In Sect. 2.2, we discuss complex Norden manifolds.
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Gerald Schubert,Georg Hager,Holger Fehsketheir operations. These “engineered” systems are designed and developed using a variety of methods for analysis, testing and evaluation that rely heavily on mathematical models that describe the inanimate systems involved and the environment in which the system operates. The desirability, if not the
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K. Waldherr,T. Huckle,T. Auckenthaler,U. Sander,T. Schulte-Herbrüggenvery complex systems in highly dynamic environments. However, the growing complexity of the tactical environment is keeping pace with the ability of new automation technologies to deal with it, producing a constant tension between the economic and practical forces that drive crew size reduction and
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Atanas Atanasov,Hans-Joachim Bungartz,Jérôme Frisch,Miriam Mehl,Ralf-Peter Mundani,Ernst Rank,Christn this paper, the latter technique is emphasized. The architecture (including the artificial intelligence components) and validation data for a particular model are presented. The components of the predesign process are illustrated in Fig. 1. This process has evolved from, and been applied to a vari
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