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8篇 您的检索式：作者名="RanB"

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		题名	作者	年代	出处	被引量
	1	A New Class of Instantaneous Dynamic User-Optimal Traffic Assignment Models显示文摘	RANB BOYCE D E LEBLANC L J	1993	Operations Research1993，41，1：	1
	2	Hemangioma of skeletal muscle显示文摘	Wild AT Ranb P Krauspe R	2000	Arch Orthop Trauma Surg2000，12，：	1
	3	EMG-biofcedhack assisted pelvic floor muscle training is an effective therapy of stress urinary or mixed incontinence:a 7-year experience with 390 patients显示文摘	Dannecker C Wolf V Ranb R	2005	Arch Gyeeol Obstet2005，273，2：	1
	4	Analysis of influencing factors on operating resistance of machine-soil system显示文摘	Wang Jiasheng Yang Ranbing Shang Shuqi	2012	Advanced Materials Research2012，422，1：	1
	5	Early severe acute pancreatities : Charateristics of a new subgroup 显示文摘	Isenmann R RanB Beger HG	2001	Pancreas2001，22，3：	1
	6	Hemangioma of skeletal muscle显示文摘	WildAT Ranb Krauspe R	2000	Arch Orthop Trauma Surg2000，12，：	1
	7	The effect of Aloe vera gel/mild soap versus mild soap aloe in preventing skin reactions in patients undergoing radiation therapy 显示文摘	Olsen DL Ranb W Bradley C	2001	Oncol Nuts Forun2001，28，3：	1
	8	Identification model of multi-layered neural network parameters and its applications in the petroleum production显示文摘This paper creates a LM (Levenberg-Marquardt) algorithm model which is appropriate to solve the problem about weights value of feedforward neural network. On the base of this model, we provide two applications in the oilfield production. Firstly, we simulated the functional relationships between the petrophysical and electrical properties of the rock by neural networks model, and studied oil saturation. Under the precision of data is confirmed, this method can reduce the number of experiments. Secondly, we simulated the relationships between investment and income by the neural networks model, and studied invest saturation point and income growth rate. It is very significant to guide the investment decision. The research result shows that the model is suitable for the modeling and identification of nonlinear systems due to the great fit characteristic of neural network and very fast convergence speed of LM algorithm.	Liu Ranbing Liu Leiming Zhang Faqiang Li Changhua	2008	Engineering Sciences2008，6，2：	0

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