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在“Elsevier电子期刊”中，命中：7,222条，耗时：0.0679666 秒

在所有数据库中总计命中：78,012条

1.Feature selection and multiple kernel boosting framework based on PSO with mutation mechanism for hyperspectral classification

作者：Chengming Qi^a ; ^b ; ^{chming.qi@gmail.com}Author Vitae ; Zhangbing Zhou^a ; ^c ; ^{zhangbing.zhou@gmail.com}Author Vitae ; Yunchuan Sun^dAuthor Vitae ; Houbing Song^e ; ^{Houbing.Song@mail.wvu.edu}Author Vitae ; Lishuan Hu^a ; ^b ; ^{hulishuan@163.com}Author Vitae ; Qun Wang^a ; ^{qunw@cugb.edu.cn}Author Vitae

关键词：Ensemble learning ; Feature selection ; Hyperspectral remote sensing image ; Multiple kernel boosting

刊名：Neurocomputing

出版年：2017

2.An interactive approach for multiple criteria selection problem

作者：Ö ; zgü ; r Ö ; zpeynirci^a ; ^{ozgur.ozpeynirci@ieu.edu.tr} ; Selin Ö ; zpeynirci^b ; Anıl Kaya^c

关键词：Multiple criteria selection problem ; Convex cone ; Interactive approach

刊名：Computers & Operations Research

出版年：2017

3.MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation

作者：A.W.C. Faria^a ; F.G.F. Coelho^a ; A.M. Silva^b ; H.P. Rocha^a ; G.M. Almeida^c ; A.P. Lemos^a ; A.P. Braga^a ;

关键词：Multiple instance learning ; KDE ; Instance selection ; Instance ranking

刊名：Engineering Applications of Artificial Intelligence

出版年：2017

4.Risk-based material selection process supported on information theory: A case study on industrial gas turbine

作者：Arian Hafezalkotob^a ; Ashkan Hafezalkotob^b ; ^{a_hafez@azad.ac.ir} ; ^{hafezalkotob@alumni.iust.ac.ir}

关键词：Risk-based fuzzy axiomatic design approach ; Multiple attribute decision making ; Shannon entropy ; Material selection ; Gas turbine

刊名：Applied Soft Computing

出版年：2017

5.Interval target-based VIKOR method supported on interval distance and preference degree for machine selection

作者：Arian Hafezalkotob^a ; Ashkan Hafezalkotob^b ; ^{a_hafez@azad.ac.ir}

关键词：Multiple attribute decision making ; VIKOR ; Target-based attributes ; Interval distance ; Preference degree ; Machine selection

刊名：Engineering Applications of Artificial Intelligence

出版年：2017

6.An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment

作者：Jindong Qin^a ; ^{qinjindongseu@126.com} ; Xinwang Liu^b ; Witold Pedrycz^c ; ^d ; ^e

关键词：Multiple criteria analysis ; Green supplier selection ; TODIM method ; Interval type-2 fuzzy sets ; Group decision making

刊名：European Journal of Operational Research

出版年：2017

7.Guided wave-based identification of multiple cracks in beams using a Bayesian approach

作者：Shuai He ; Ching-Tai Ng ; ^{alex.ng@adelaide.edu.au" class="auth_mail" title="E-mail the corresponding author}

关键词：Multiple cracks ; Damage identification ; Bayesian statistical framework ; Bayesian model class selection ; Guided waves ; Spectral finite element ; Mode conversion

刊名：Mechanical Systems and Signal Processing

出版年：2017

8.A new multiple seeds based genetic algorithm for discovering a set of interesting Boolean association rules

作者：Mir Md. Jahangir Kabir ; ^{mmjkabir@utas.edu.au} ; Shuxiang Xu ^{Shuxiang.Xu@utas.edu.au} ; Byeong Ho Kang ^{Byeong.Kang@utas.edu.au} ; Zongyuan Zhao ^{Zongyuan.Zhao@utas.edu.au}

关键词：Multiple seeds based genetic algorithm ; Initial population ; Boolean association rules ; Conditional probability ; Search efficiency

刊名：Expert Systems with Applications

出版年：2017

9.A new optimal feature selection algorithm for classification of power quality disturbances using discrete wavelet transform and probabilistic neural network

作者：Suhail Khokhar^a ; ^b ; ^{suhail@quest.edu.pk} ; Abdullah Asuhaimi Mohd Zin^a ; Aslam Pervez Memon^b ; Ahmad Safawi Mokhtar^a

关键词：Power quality disturbances ; Feature extraction ; Optimal feature selection ; Discrete wavelet transform ; Artificial bee colony ; Probabilistic neural network

刊名：Measurement

出版年：2017

10.A multi-kernel based framework for heterogeneous feature selection and over-sampling for computer-aided detection of pulmonary nodules

作者：Peng Cao^a ; ^b ; ^{caopeng@cse.neu.edu.cn}Author Vitae ; Xiaoli Liu^a ; ^bAuthor Vitae ; Jinzhu Yang^aAuthor Vitae ; Dazhe Zhao^a ; ^bAuthor Vitae ; Wei Li^bAuthor Vitae ; Min Huang^c ; ^dAuthor Vitae ; Osmar Zaiane^eAuthor Vitae

关键词：Lung nodule detection ; False positive reduction ; Classification ; Imbalanced data learning ; Multi-kernel learning ; Feature selection

刊名：Pattern Recognition

出版年：2017

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