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8篇 您的检索式：作者名="Hanea"

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		题名	作者	年代	出处	被引量
	1	Granulocyte macrophage colony-stimulating factor promotes regeneration of retinal ganglion cells in vitro through a mammalian target of rapamycin-dependent mechanism显示文摘	Legacy J Hanea S Theoret J		0，，：	1
	2	Irreversible membrane fouling during ultrafiltration of surface water 显示文摘	KIMURA K HANEA Y WATANABEA Y	2004	Water Res2004，38，1415：	1
	3	Application of the representer method for parameter estimation in numerical reservoir models显示文摘	Przyhysz-Jarnut J K Hanea R G Jansen J D	2007	Computational Geosciences2007，11，1：	1
	4	Hybrid method for quantifying and analyzing bayesian belief nets 显示文摘	Hanea A M Kurowicka D Cooke R M	2006	Quality and Reliability Engineering2006，22，6：	1
	5	Effects of hydrostatic pressure on matrix synthesis and matrix metalloproteinase production in the human lumbar intervertabral disc 显示文摘	Hanea T Ishihara H Ohshima H	1997	Spine1997，22，9：	1
	6	Irreversible membrane fouling during ultrafiltration of surface water 显示文摘	Kimuraa K Hanea Y Watanabe Y	2004	Water Research2004，38，12：	1
	7	Effects of hydrostatic pressure on matrix synthesis and matrix metalloproteinase production in the human lumbar intervertabral disc显示文摘	Hanea T Ishihara H Ohshima H	1997	Spine1997，22，：	1
	8	Application of machine learning to assess the value of information in polymer flooding显示文摘In this work,we provide a more consistent alternative for performing value of information(VOI)analyses to address sequential decision problems in reservoir management and generate insights on the process of reservoir decision-making.These sequential decision problems are often solved and modeled as stochastic dynamic programs,but once the state space becomes large and complex,traditional techniques,such as policy iteration and backward induction,quickly become computationally demanding and intractable.To resolve these issues and utilize fewer computational resources,we instead make use of a viable alternative called approximate dynamic programming(ADP),which is a powerful solution technique that can handle complex,large-scale problems and discover a near-optimal solution for intractable sequential decision making.We compare and test the performance of several machine learning techniques that lie within the domain of ADP to determine the optimal time for beginning a polymer flooding process within a reservoir development plan.The approximate dynamic approach utilized here takes into account both the effect of the information obtained before a decision is made and the effect of the information that might be obtained to support future decisions while significantly improving both the timing and the value of the decision,thereby leading to a significant increase in economic performance.	Amine Tadjer Reidar B.Bratvold Aojie Hong Remus Hanea	2021	Petroleum Research2021，6，4：	0

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