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11篇 您的检索式：作者名="Arbaoui"

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		题名	作者	年代	出处	被引量
	1	Qualification of Three Analytical Wake Models显示文摘	Naima Charhouni Mohammed Sallaou Abdelaziz Arbaoui	2016	Journal of Mechanics Engineering and Automation2016，6，4：	2
	2	Numerical simulation of the one-dimensional incommensurate charge density wave dynamics显示文摘	Qjani M Arbaoui A Ayadi A	1998	Synthetic Metals1998，96，2：	1
	3	A Comparative Review of Process-centered Software Engineering Environments显示文摘	Arbaoui S Derniame J C Oquendo F Verjus H	2002	Annals of Software Engineering2002，14，1：	1
	4	Bimetallic copper(II) and zinc(II) complexes of aeyclie Sehiff base ligands derived from amino acids 显示文摘	Arbaoui A Redshaw C Noelia M S B	2011	Inorganica Chimica Acta2011，365，1：	1
	5	High affinity and selectivity of some tetrahydroprotoberberine alkaloids for rat striatal ^3H-raclopride binding sites 显示文摘	Cortes D Arbaoui J Protais P	1993	Nat Prod Lett1993，3，4：	1
	6	查看详情显示文摘	Arbaoui A Redshaw C		0，，：	1
	7	Adsorption of Cesium From Aqueous Solution on Binary Mixture of Iron Pillared Layered Montmorillonite and Goethite 显示文摘	Ararem A Bouras O Arbaoui F	2011	Chemical Engineering Journal2011，172，：	1
	8	Adsorption of caesium from aqueous solution on binary mixture of iron pillared layered montmorillonite and goethite显示文摘	Ararem A Bouras O Arbaoui F	2011	Chem Eng J2011，172，1：	1
	9	Predictive functional control of a counter current heat exchanger using convex- ity property 显示文摘	Abdelghani-ldrissi M A Arbaoui M A Estel L	2001	Chemical Engineering and Processing : Process Intensification2001，40，5：	1
	10	324 Troponin in Emergency Department: an overused test for patient screening without clinical suspicion of acute coronary syndrome 显示文摘	NALLET O ARBAOUI S GRENIER A	2011	Arch Cardiovasc Dis Suppl2011，3，1：	1
	11	Developing a multi-label tinyML machine learning model for an active and optimized greenhouse microclimate control from multivariate sensed data显示文摘In the uncertainties within which the worldwide food security lies nowadays,the agricultural industry is raising a crucial need for being equipped with the state-of-the-art technologies for a more efficient,climate-resilient and sustainable production.The traditional production methods have to be revisited,and opportunities should be given for the innovative solutions henceforth brought by big data analytics,cloud computing and internet of things(IoT).In this context,we develop an optimized tinyML-oriented model for an active machine learningbased greenhouse microclimate management to be integrated in an on-field microcontroller.We design an experimental strawberry greenhouse from which we collect multivariate climate data through installed sensors.The obtained values'combinations are labeled according to a five-action multi-label control strategy,then used to prepare a machine learning-ready dataset.The dataset is used to train and five-fold cross-validate 90 Multi-Layer Perceptrons(MLPs)with varied hyperparameters to select the most performant–yet optimized–model instance for the addressed task.Our multi-label control approach enables designing highly scalable models with reduced computational complexity,comprising only n control neurons instead of(1+∑n k=1Cn k)neurons(usually generated from a classic single-label approach from n input variables).Our final selected model incorporates 2 hidden layers with 7 and 8 neurons respectively and 151 parameters;it scored a mean accuracy of 97%during the cross-validation phase,then 96%on our supplementary test set.The model enables an intelligent and autonomous greenhouse management with the less required computations.It can be efficiently deployed in microcontrollers within real world operating conditions.	Ilham Ihoume Rachid Tadili Nora Arbaoui Mohamed Benchrifa Ahmed Idrissi Mohamed Daoudi	2022	Artificial Intelligence in Agriculture2022，，1：	0

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