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Titlebook: Applied Decision Analysis; Francisco Javier Girón Book 1998 Springer Science+Business Media New York 1998 calculus.ecosystem.linear optimi

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21#
發(fā)表于 2025-3-25 04:52:10 | 只看該作者
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23#
發(fā)表于 2025-3-25 12:34:52 | 只看該作者
24#
發(fā)表于 2025-3-25 17:46:36 | 只看該作者
https://doi.org/10.1007/978-3-8348-9955-2rmacokinetic/pharmacodynamic models, growth curve models, and repeated measurement models. The discussion will be focused on a specific application. We consider optimal design of apheresis schedules to collect blood stem cells from cancer patients. Blood stem cells are collected prior to the patient
25#
發(fā)表于 2025-3-25 20:31:04 | 只看該作者
Team building and giving/receiving feedback,support system integrating the beliefs and preferences of members of a neonatology service. In this paper, we introduce one such system called IctNeo. We describe first the basic representation of the problem by means of influence diagrams, including admission and treatment decisions. The correspond
26#
發(fā)表于 2025-3-26 00:55:15 | 只看該作者
Giving presentations with impact, the decision maker (DM) who has imprecise information and/or expresses his/her considerations subjectively, or by statistical inference from past data and, consequently, their stability is doubtful. Therefore, it is reasonable to construct a model reflecting imprecise data or ambiguity in terms of
27#
發(fā)表于 2025-3-26 05:34:08 | 只看該作者
Team building and giving/receiving feedback,chastic process, and extends previous results obtained for static models in the literature. Two interesting applications of this theory can be considered. First, the measure of the cross-market arbitrage gives information about the integration between two or more financial markets. Second, dynamic a
28#
發(fā)表于 2025-3-26 10:23:16 | 只看該作者
29#
發(fā)表于 2025-3-26 14:44:51 | 只看該作者
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30#
發(fā)表于 2025-3-26 19:25:32 | 只看該作者
https://doi.org/10.1007/978-3-540-77127-2Factors like multiple uncertainty sources, multiple objectives, time-effects over preferences and the hierarchical nature of the planning process increase the complexity of reservoir management problems. We describe developments in a methodology for reservoir operations and its implementation in an intelligent decision support system.
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