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Titlebook: Klinische Endokrinologie für Frauen?rzte; Thomas Strowitzki,Olaf Ortmann Book 2024Latest edition Der/die Herausgeber bzw. der/die Autor(en

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41#
發(fā)表于 2025-3-28 17:01:48 | 只看該作者
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42#
發(fā)表于 2025-3-28 18:53:03 | 只看該作者
https://doi.org/10.1007/978-3-662-65517-7Endokrinologie; Gyn?kologie; HRT; Kontrazeption; Menopause; Reproduktionsmedizin; Hormone; Ovarfunktion; Sch
43#
發(fā)表于 2025-3-29 02:52:43 | 只看該作者
44#
發(fā)表于 2025-3-29 03:42:42 | 只看該作者
45#
發(fā)表于 2025-3-29 10:03:50 | 只看該作者
in manufacturing systems. This paper focuses on a dynamic JSS problem to minimise the total weighted tardiness. In dynamic JSS, attributes of a job are only revealed after it arrives at the shop floor. Dispatching rule heuristics are prominent approaches to dynamic JSS problems, and Genetic Programm
46#
發(fā)表于 2025-3-29 12:17:52 | 只看該作者
47#
發(fā)表于 2025-3-29 15:47:43 | 只看該作者
T. Gudermann,I. Boekhoffimate of the input probability density function, based on the one-class input data. This can be used for anomaly detection: query points are classed as anomalies if their density is below some threshold. The disadvantage is that kernel density estimation is lazy, that is the bulk of the computation
48#
發(fā)表于 2025-3-29 21:37:51 | 只看該作者
O. Hiort,T. Strowitzkimultaneously a solution and sub-parts of it within a GP framework. This problem is a crucial point in GP research lately since this is intimately linked with building blocks existence problem. Thus, in this paper, we present an “on-going” work concerning .. — Dynamic Lattice Genetic Programming— a n
49#
發(fā)表于 2025-3-30 01:50:11 | 只看該作者
M. Ludwig,J. M. Weissning of multiple joint parameters of the manipulator to reach a desired position in the Cartesian space. We present a new approach to identify a closed-form solution for the Inverse Kinematics (IK) problem, namely IK-CCGP. The novelty of IK-CCGP is the cooperative coevolutionary learning strategy. U
50#
發(fā)表于 2025-3-30 06:43:30 | 只看該作者
M. Ludwig real-world software development this method could also be used, as a programmer could first define the input/output examples for a certain problem and then let genetic programming generate the functional source code. However, a prerequisite for using genetic programming as support system in real-wo
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