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在“Elsevier电子期刊”中，命中：3,410条，耗时：0.0489773 秒

在所有数据库中总计命中：14,094条

1.A joint stochastic-deterministic approach for long-term and short-term modelling of monthly flow rates

作者：Milan Stojković^a ; ^{milan.stojkovic@jcerni.co.rs} ; Srđan Kostić^a ; Jasna Plav&scaron ; ić^b ; Stevan Prohaska^a

关键词：Joint stochastic-deterministic modelling ; Cross-correlation transfer function ; Artificial neural network ; Polynomial regression ; Climatic input ; The Great Morava River

刊名：Journal of Hydrology

出版年：2017

2.Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression

作者：Nzooma M. Shimaponda-Mataa^a ; ^b ; ^{nzomataa@gmail.com} ; Enala Tembo-Mwase^c ; Michael Gebreslasie^d ; Thomas N.O. Achia^e ; Samson Mukaratirwa^b

关键词：R-INLA ; R version of integrated Laplace ; NDVI ; normalised difference vegetation index ; WHO ; World Health Organisation ; LS ; Lusaka ; LP ; Luapula ; NW ; North-western ; W ; Western ; CSO ; Central Statistical Office ; HMIS ; Health Management Information System ; MOH ; Ministry of Health ; LST ; land surface temperature ; MODIS ; Moderate Resolution Imaging Spectroradiometer ; USGS ; U. S. Geological Survey ; LP DAAC ; Land Processes Distributed Active Archive Centre ; CHIRPS ; Climate Hazards Group InfraRed Precipita

刊名：Acta Tropica

出版年：2017

3.A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning

作者：D. Lorente ; ^a ; ^{delia.lorente@uv.es} ; F. Martí ; nez-Martí ; nez^a ; ^{francisco.martinez-martinez@uv.es} ; M.J. Rupé ; rez^b ; ^{mjrupere@upvnet.upv.es} ; M.A. Lago^c ; ^{Miguel.Lago@psych.ucsb.edu} ; M. Martí ; nez-Sober^a ; ^{marcelino.martinez@uv.es} ; P. Escandell-Montero^a ; ^{pablo.escandell@uv.es} ; J.M. Martí ; nez-Martí ; nez^a ; ^{jose.maria.martinez@uv.es} ; S. Martí ; nez-Sanchis^b ; ^{sanmars1@upv.es} ; A.J. Serrano-Ló ; pez^a ; ^{antonio.j.serrano@uv.es} ; C. Monserrat^c ; ^{cmonserr@dsic.upv.es} ; J.D. Martí ; n-Guerrero^a ; ^{jose.d.martin@uv.es}

关键词：Soft tissue deformation ; Biomechanical behaviour ; Liver ; Machine learning ; Tree-based regression

刊名：Expert Systems with Applications

出版年：2017

4.A hybrid particle swarm optimization and support vector regression model for modelling permeability prediction of hydrocarbon reservoir

作者：Kabiru. O. Akande^a ; ^{koakande@gmail.com} ; Taoreed. O. Owolabi^b ; ^e ; ^{owolabitaoreedolakunle@gmail.com} ; Sunday. O. Olatunji^c ; ^{oluolatunji.aadam@gmail.com} ; AbdulAzeez AbdulRaheem^d ; ^{aazeez@kfupm.edu.sa}

关键词：Particle swarm optimization (PSO) ; Support vector regression (SVR) ; Hydrocarbon reservoir ; Permeability prediction ; Optimization techniques

刊名：Journal of Petroleum Science and Engineering

出版年：2017

5.Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models

作者：Beatriz Leal De Rivas^a ; José ; -Luis Vivancos^b ; ^c ; ^d ; ^{jvivanco@dpi.upv.es} ; Joaquí ; n Ordieres-Meré ; ^e ; Salvador F. Capuz-Rizo^b

关键词：Aircraft turbine ; Engine oil ; Total acid number (TAN) ; FTIR ; Regression models

刊名：Chemometrics and Intelligent Laboratory Systems

出版年：2017

6.Grey-box model for pipe temperature based on linear regression

作者：Richá ; rd Kicsiny ^{Kicsiny.Richard@gek.szie.hu}

关键词：Pipe temperature ; Mathematical modelling ; Linear regression ; Grey-box model

刊名：International Journal of Heat and Mass Transfer

出版年：2017

7.Rare earth element geochemistry of shallow carbonate outcropping strata in Saudi Arabia: Application for depositional environments prediction

作者：Hassan A. Eltom^a ; ^b ; ^{heltom@ku.edu} ; Osman M. Abdullatif^a ; Mohammed H. Makkawi^a ; Isam-Eldin A. Eltoum^c

关键词：Carbonates ; Outcrop analog ; Facies modelling ; Arab-D reservoir ; Logistic regression

刊名：Sedimentary Geology

出版年：2017

8.Improving sustainable office building operation by using historical data and linear models to predict energy usage

作者：Majeed Safa^a ; ^{Majeed.Safa@lincoln.ac.nz} ; Mahdi Safa^b ; Jeremy Allen^c ; Arash Shahi^d ; Carl T. Haas^e

关键词：Energy modelling ; Energy auditing ; Office buildings ; Energy saving ; Artificial neural network ; Linear regression model

刊名：Sustainable Cities and Society

出版年：2017

9.Robust estimators in semi-functional partial linear regression models

作者：Graciela Boente^a ; ^b ; ^{gboente@dm.uba.ar} ; Alejandra Vahnovan^c ; ^d ; ^{avahnovan@gmail.com}

关键词：62G35 ; 62G08 ; 62G05

刊名：Journal of Multivariate Analysis

出版年：2017

10.Application of artificial neural networks to the forecasting of dissolved oxygen content in the Hungarian section of the river Danube

作者：Anita Csá ; brá ; gi^a ; ^{csabragi.anita@gmail.com} ; ^{csabragi.anita@gek.szie.hu} ; Sá ; ndor Molná ; r^a ; ^{molnar.sandor@gek.szie.hu} ; Pé ; ter Tanos^a ; ^{tanospeter@gmail.com} ; Jó ; zsef Ková ; cs^b ; ^{kevesolt@gmail.com}

关键词：ANN ; Artificial Neural Network ; CA ; CB ; CC ; CD ; Combination A ; B ; C ; D ; DO ; dissolved oxygen ; EC ; electrical conductivity ; GRNN ; General Regression Neural Network ; hydro PP ; hydro power plant ; HNPP ; Hungarian Nuclear Power Plant ; IA ; Willmott&rsquo ; s index of agreement ; MAE ; mean absolute error ; MLPNN ; Multilayer Perceptron Neural Network ; MLR ; Multivariate Linear Regression ; R2 ; coefficient of determination ; RBFNN ; Radial Basis Function Neural Network ; RF ; runoff ; rkm ; river kilometres ; RMSE ; r

刊名：Ecological Engineering

出版年：2017

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