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在“Elsevier电子期刊”中，命中：41,999条，耗时：0.2358606 秒

在所有数据库中总计命中：579,534条

1.Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs

作者：S. Suriadi^a ; ¹ ; ^{s.suriadi@qut.edu.au} ; R. Andrews^a ; ^{r.andrews@qut.edu.au} ; A.H.M. ter Hofstede^a ; ^b ; ^{a.terhofstede@qut.edu.au} ; M.T. Wynn^a ; ^{m.wynn@qut.edu.au}

关键词：Process mining ; Data mining ; Data quality ; Event log quality ; Patterns ; Systematic data pre-processing ; Event log preparation

刊名：Information Systems

出版年：2017

2.Application of logical analysis of data to machinery-related accident prevention based on scarce data

作者：Sabrina Jocelyn^a ; ^b ; ^{sabjoc@irsst.qc.ca} ; Yuvin Chinniah^b ; Mohamed-Salah Ouali^b ; Soumaya Yacout^b

关键词：Machinery safety ; Accident ; Prevention ; Logical Analysis of Data (LAD) ; Pattern recognition ; Risk management

刊名：Reliability Engineering & System Safety

出版年：2017

3.Factors affecting coalbed methane (CBM) well productivity in the Shizhuangnan block of southern Qinshui basin, North China: Investigation by geophysical log, experiment and production data

作者：Cheng Peng^a ; ^b ; Changchun Zou^a ; ^b ; ^{zoucc@cugb.edu.cn} ; Tianning Zhou^a ; ^b ; Kang Li^a ; ^b ; Yuqing Yang^c ; Guohua Zhang^c ; Wenwen Wang^c

关键词：Coalbed methane (CBM) ; Geophysical log data ; Qinshui basin ; Production characteristic ; Roof and floor of coal seam

刊名：Fuel

出版年：2017

4.Sampled-data fuzzy control for a class of nonlinear systems with missing data and disturbances

作者：Wenhui Liu^a ; ^b ; Cheng-Chew Lim^b ; Peng Shi^b ; ¹ ; ^{peng.shi@adelaide.edu.au" class="auth_mail" title="E-mail the corresponding author} ; Shengyuan Xu^a

关键词：Fuzzy logic systems ; Sampled-data control ; State observer ; Disturbance observer ; Missing input data

刊名：Fuzzy Sets and Systems

出版年：2017

5.Data classification with binary response through the Boosting algorithm and logistic regression

作者：Fortunato S. de Menezes ; ^a ; ^b ; ^{fmenezes@dfi.ufla.br" class="auth_mail" title="E-mail the corresponding author} ; ^{fsdmenezes@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Gilberto R. Liska^b ; ^{gilbertoliska@unipampa.edu.br" class="auth_mail" title="E-mail the corresponding author} ; Marcelo A. Cirillo^b ; ^{macufla@dex.ufla.br" class="auth_mail" title="E-mail the corresponding author} ; Má ; rio J.F. Vivanco^b ; ^{ferrua@dex.ufla.br" class="auth_mail" title="E-mail the corresponding author}

关键词：Boosting algorithm ; Data classification ; Logistic regression ; Information criteria ; AIC ; BIC ; Selection of models ; Monte Carlo Simulation

刊名：Expert Systems with Applications

出版年：2017

6.A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis

作者：Ziqiang Zeng^a ; ^b ; ^c ; Wenbo Zhu^c ; Ruimin Ke^c ; John Ash^c ; Yinhai Wang^c ; ^{yinhai@u.washington.edu} ; Jiuping Xu^b ; Xinxin Xu^a ; ^b

关键词：Generalized nonlinear model ; Mixed multinomial logit ; Crash frequency ; Crash severity ; Traffic safety

刊名：Accident Analysis & Prevention

出版年：2017

7.Generating automatic linguistic descriptions with big data

作者：Patricia Conde-Clemente ; ^a ; ^{condepatricia@uniovi.es} ; Gracian Trivino^b ; ^{gracian.trivino@phedes.com} ; Jose M. Alonso^c ; ^{josemaria.alonso.moral@ucs.es}

关键词：Linguistic descriptions ; Big data ; MapReduce ; Fuzzy logic

刊名：Information Sciences

出版年：2017

8.An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities

作者：Hai Wang^a ; ^{wanghai17@sina.com} ; Zeshui Xu^a ; ^b ; ^{xuzeshui@263.net} ; Witold Pedrycz^c ; ^d ; ^e ; ^{wpedrycz@ualberta.ca}

关键词：Big data ; Data-intensive science ; Fuzzy sets ; Fuzzy logic ; Granular computing

刊名：Knowledge-Based Systems

出版年：2017

9.Indexing Next-Generation Sequencing data

作者：Vahid Jalili ; ^{vahid.jalili@polimi.it}Author Vitae ; Matteo MatteucciAuthor Vitae ; Marco MasseroliAuthor Vitae ; Stefano CeriAuthor Vitae

关键词：Genomic computing ; Domain-specific data indexing ; Region-based operations and calculus ; Data integration

刊名：Information Sciences

出版年：2017

10.Oddness/evenness-based classifiers for Boolean or numerical data

作者：Myriam Bounhas^a ; ^b ; ^{Myriam_Bounhas@yahoo.fr} ; Henri Prade^c ; ^d ; ^{prade@irit.fr} ; Gilles Richard^c ; ^{richard@irit.fr}

关键词：Logical proportion ; Classification ; Boolean data ; Numerical data ; k-Nearest neighbors method

刊名：International Journal of Approximate Reasoning

出版年：2017

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