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54篇 您的检索式：作者名="KUSIAK Andrew"

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	题名	作者	年代	出处	被引量
1	Rough Set Theory:a Data Mining Tool for Semiconductor Manufacturing显示文摘	Andrew Kusiak	2001	IEEE Transactions on Electronics Packaging Manufacturing2001，24，1：	1
2	Dependency analysis in constraint negotiation显示文摘	ANDREW Kusiak JUITE Wang	1995	IEEE Transaction on Systems Man and Cybernetics1995，25，9：	1
3	A structured approach for analysis of design processes显示文摘	ANDREW Kusiak JUITE Wang DAVID W He	1995	IEEE Transactions on Components Packaging and Manufacturing Technology(Part A)1995，18，3：	1
4	Modeling an Innovation Ecosystem with Adaptive Agents 显示文摘	ENGLER JOSEPH KUSIAK ANDREW	2011	lnternational Journal of Innovation Science2011，，3：	1
5	Short-horizon prediction of wind power: A data-driven approach显示文摘	Kusiak Andrew	2010	IEEE Transactions on Ener- gy Conversion2010，25，4：	1
6	Scheduling manufacturing systems in an agile environment显示文摘	David He Astghik Babayan Andrew Kusiak	2001	Robotics and Computer Integrated Manufacturing2001，17，：	1
7	Rough Set Theory:A Data Mining Tool for Semiconductor Manuf acturing显示文摘	Andrew Kusiak	2001	IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANU FACTURING2001，24，1：	1
8	Overview of Kanban Systems 显示文摘	Chun-Che Huang Andrew Kusiak	1996	International Journal of Computer Integrated Manufacturing1996，9，3：	1
9	Short-term prediction of wind power with a clustering approach显示文摘	Kusiak Andrew LiWenyan	2010	Renewable Energy(S0960-1481)2010，35，10：	1
10	Analyzing bearing faults in wind turbines:a data-mining approach显示文摘	Andrew Kusiak Anoop Verma	2012	Renewable Energy2012，48，：	1
11	Models for monitoring wind farm power显示文摘	Andrew Kusiak Haiyang Zheng Zhe Song	2008	Renewable Energy2008，，3：	1
12	Development of modular products显示文摘	Andrew Kusiak Huang chun che	1996	IEEE Transactions on Components Packa- ging and Manufacturing Technology Part A1996，19，4：	1
13	Active label-denoising algorithm based on broad learning for annotation of machine health status显示文摘Deep learning has led to tremendous success in machine maintenance and fault diagnosis.However,this success is predicated on the correctly annotated datasets.Labels in large industrial datasets can be noisy and thus degrade the performance of fault diagnosis models.The emerging concept of broad learning shows the potential to address the label noise problem.Compared with existing deep learning algorithms,broad learning has a simple architecture and high training efficiency.An active label denoising algorithm based on broad learning(ALDBL)is proposed.First,ALDBL captures the embedded representation from the time-frequency features by a recurrent memory cell.Second,it augments wide features with a sparse autoencoder and projects the sparse features into an orthogonal space.A proposed corrector then iteratively changes the weights of source examples during the training and corrects the labels by using a label adaptation matrix.Finally,ALDBL finetunes the model parameters with actively sampled target data with reliable pseudo labels.The performance of ALDBL is validated with three benchmark datasets,including 30 label denoising tasks.Computational results demonstrate the effectiveness and advantages of the proposed algorithm over the other label denoising algorithms.	LIU GuoKai SHEN WeiMing GAO Liang KUSIAK Andrew	2022	Science China(Technological Sciences)2022，65，9：	1
14	Design of wind farm layout for maximum wind energy capture显示文摘	Andrew Kusiak Zhe Song	2009	Renewable Energy2009，，3：	1
15	Scheduling manufacturing systems in an agile environment显示文摘	David He Astghik Babayan Andrew Kusiak	2001	Robotics and Computer Integrated Manufacturing2001，17，：	1
16	Data mining in design of products and production systems 显示文摘	Andrew Kusiak Matthew Smith	2007	Annual Reviews in Control2007，31，1：	1
17	Wind farm power prediction: A data-mining approach显示文摘	Andrew Kusiak Zheng Haiyang Song Zhe	2009	Wind Energy2009，12，3：	1
18	Reengineering of design and manufacturing process显示文摘	Andrew Kusiak T Nick Larson Juite Wang	1994	Computers Ind Engng1994，26，3：	1
19	Forming teams: an analytical approach显示文摘	ARMEN Zzkarian ANDREW Kusiak	1999	IIE Transactions1999，，1：	1
20	A data-driven approach for steam load prediction in buildings显示文摘	Andrew Kusiak Mingyang Li Zijun Zhang	2009	Applied Energy2009，，3：	1

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