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Titlebook: Advances in Stochastic and Deterministic Global Optimization; Panos M. Pardalos,Anatoly Zhigljavsky,Julius ?ilin Book 2016 Springer Intern

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樓主: Hypothesis
51#
發(fā)表于 2025-3-30 11:34:25 | 只看該作者
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Combining Interval and Probabilistic Uncertainty: What Is Computable?ntities. In these computations, it is important to take into account that measurement results are never absolutely exact, that there is always measurement uncertainty, because of which the measurement results are, in general, somewhat different from the actual (unknown) values of the corresponding q
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發(fā)表于 2025-3-31 07:38:00 | 只看該作者
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Assessing Basin Identification Methods for Locating Multiple Optima this task is obtaining topographical information about the objective function from a discrete sample of the search space and representing it in a graph structure. So far, different variants of this approach are usually assessed by evaluating the performance of a whole optimization algorithm using t
58#
發(fā)表于 2025-3-31 15:05:32 | 只看該作者
Cloud Computing Approach for Intelligent Visualization of Multidimensional Dataate visualization models based on the best practices and experience. A new Cloud computing-based data mining system DAMIS is introduced for the intelligent data analysis including data visualization methods. It can assist researchers to handle large amounts of multidimensional data when executing re
59#
發(fā)表于 2025-3-31 19:05:04 | 只看該作者
Comparative Study of Different Penalty Functions and Algorithms in Survey Calibrationocess is an optimization procedure, for which a variety of penalty functions can be used. In this chapter, we consider three of the classical penalty functions that are implemented in many of the standard calibration software packages. We present two algorithms used by many of these software package
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