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compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regressionspline

Ali Reza GHANIZADEH, Morteza RAHROVAN

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 4,   Pages 787-799 doi: 10.1007/s11709-019-0516-8

Abstract: compressive strength (UCS) of soil-RAP blend stabilized with Portland cement based on multivariate adaptive regressionspline (MARS).

Keywords： soil-reclaimed asphalt pavement blend     Portland cement     unconfined compressive strength     multivariate adaptive regressionspline    

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Interactive image segmentation with a regression based ensemble learning paradigm Article

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 1002-1020 doi: 10.1631/FITEE.1601401

Abstract: This paper presents a novel interactive image segmentation method via a regression-based ensemble modelThe task is formulated as a non-linear problem integrating two complementary spline regressors and strengtheningFirst, two spline regressors with a complementary nature are constructed based on multivariate adaptiveregression splines (MARS) and smooth thin plate spline regression (TPSR).Next, a support vector regression (SVR) based decision fusion model is adopted to integrate the results

Keywords： Interactive image segmentation     Multivariate adaptive regression splines (MARS)     Ensemble learning     Thin-platespline regression (TPSR)     Semi-supervised learning     Support vector regression (SVR)    

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Multiresolution and multimaterial topology optimization of fail-safe structures under B-spline spaces

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 4, doi: 10.1007/s11465-023-0768-9

Abstract: This study proposes a B-spline-based multiresolution and multimaterial topology optimization (TO) designfiner density mesh to discretize the design domain, in which the density field is described by the B-splineThe B-spline can efficiently and accurately convert optimized FSSs into computer-aided design models.

Keywords： multiresolution     multimaterial     topology optimization     fail-safe structure     B-spline    

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Interpolation of a spline developable surface between a curve and two rulings

Alicia CANTÓN,Leonardo FERNÁNDEZ-JAMBRINA

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 3,   Pages 173-190 doi: 10.1631/FITEE.14a0210

Abstract: In this paper we address the problem of interpolating a spline developable patch bounded by a given splineTo complete the boundary of the patch, a second spline curve is to be given.

Keywords： Developable surfaces     Spline surfaces     Blossoms    

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Exponential polynomial uniform splines model

Zhao Yanli,Ping Ping,Liu Fengyu

Strategic Study of CAE 2008, Volume 10, Issue 7,   Pages 147-152

Abstract: style="text-align: justify;"> A new model of k( k ≥ 3) order exponential polynomial uniform splineis given.Most of its properties similar to those of the B - spline model, and also it has an adjustableThe spline curves which are constructed by the exponential polynomial uniform splines can adjust the

Keywords： exponential polynomial uniform spline function     uniform B - spline function     shape parameter    

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Crack fault quantitative diagnosis based on finite element of B-spline wavelet on the interval

XIANG Jia-wei, CHEN Xue-feng, HE Zheng-jia, HE Yu-min

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 2,   Pages 177-182 doi: 10.1007/s11465-006-0001-7

Abstract: Then, the one-dimensional crack element of B-spline wavelet on the interval (BSWI) was built to solve

Keywords： one-dimensional     B-spline     incipient     prognosis     identification precision    

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Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

Frontiers in Energy 2013, Volume 7, Issue 1,   Pages 103-110 doi: 10.1007/s11708-012-0220-z

Abstract: Then on the basis of the simulated results, the multiple regression models were developed respectivelyAccording to the analysis of regression coefficients, the appropriate building envelope design schemesAt last, the regression model evaluations consisting of the simulation evaluations and the actual caseevaluations were performed to verify the feasibility and accuracy of the regression models.It is believed that the regression models developed in this paper can be used to estimate the energy

Keywords： regression model     energy consumption     building envelope     office building     different climates    

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Dynamic response surface methodology using Lasso regression for organic pharmaceutical synthesis

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2,   Pages 221-236 doi: 10.1007/s11705-021-2061-y

Abstract: Two approaches can be adopted in the estimation of the model parameters: stepwise regression, used inseveral of previous publications, and Lasso regression, which is newly incorporated in this paper forTherefore, DRSM with Lasso regression can provide faster and more accurate data-driven models for a variety

Keywords： data-driven modeling     pharmaceutical organic synthesis     Lasso regression     dynamic response surface methodology    

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Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 5,   Pages 1181-1198 doi: 10.1007/s11709-021-0744-6

Abstract: The obtained results are then checked statistically with nonlinear multiple regression (NMR) and artificial

Keywords： interaction     load sharing ratio     piled raft     nonlinear regression     artificial neural network    

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Multivariable regression model for Fox depth correction factor

Ravi Kant MITTAL, Sanket RAWAT, Piyush BANSAL

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 103-109 doi: 10.1007/s11709-018-0474-6

Abstract: Therefore, this paper presents a non-linear regression model for the analysis of effect of embedment

Keywords： settlement     embedment     Fox depth correction factor     regression     multivariable    

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of driver-response relationships: identifying factors using a novel framework integrating quantile regression

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1676-2

Abstract:

● A novel framework integrating quantile regression with machine learning

Keywords： Driver-response     Upper boundary of relationship     Interpretable machine learning     Quantile regression    

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Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 133-136 doi: 10.1007/s11709-013-0202-1

Abstract: This article examines the capability of Gaussian process regression (GPR) for prediction of effective

Keywords： unsaturated soil     effective stress parameter     Gaussian process regression (GPR)     artificial neural network    

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Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 1,   Pages 90-99 doi: 10.1007/s11709-016-0363-9

Abstract: In this paper, considering the experimental results, three different models of multiple linear regressionevaluate the compressive strength of concrete with different mix designs, however, multiple linear regression

Keywords： concrete     28 days compressive strength     multiple linear regression     artificial neural network     ANFIS     sensitivity    

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SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 1,   Pages 185-198 doi: 10.1007/s11709-019-0591-x

Abstract: With this study, along with the conventional methods of simple and multiple linear regression models,

Keywords： undrained shear strength     linear regression     random forest     gradient boosting     machine learning     standard    

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Presentation of regression analysis, GP and GMDH models to predict the pedestrian density in various

Iraj BARGEGOL; Seyed Mohsen HOSSEINIAN; Vahid NAJAFI MOGHADDAM GILANI; Mohammad NIKOOKAR; Alireza OROUEI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 250-265 doi: 10.1007/s11709-021-0785-x

Abstract: Regression analysis was then applied to determine the relationship between SMS, flow rate, andBy the use of regression analysis, the mathematical relationships between variables in all facilities

Keywords： pedestrian density     regression analysis     GP model     GMDH model    

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Title Author Date Type Operation

compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regressionspline

Ali Reza GHANIZADEH, Morteza RAHROVAN

Journal Article

Interactive image segmentation with a regression based ensemble learning paradigm

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Journal Article

Multiresolution and multimaterial topology optimization of fail-safe structures under B-spline spaces

Journal Article

Interpolation of a spline developable surface between a curve and two rulings

Alicia CANTÓN,Leonardo FERNÁNDEZ-JAMBRINA

Journal Article

Exponential polynomial uniform splines model

Zhao Yanli,Ping Ping,Liu Fengyu

Journal Article

Crack fault quantitative diagnosis based on finite element of B-spline wavelet on the interval

XIANG Jia-wei, CHEN Xue-feng, HE Zheng-jia, HE Yu-min

Journal Article

Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

Journal Article

Dynamic response surface methodology using Lasso regression for organic pharmaceutical synthesis

Journal Article

Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based

Journal Article

Multivariable regression model for Fox depth correction factor

Ravi Kant MITTAL, Sanket RAWAT, Piyush BANSAL

Journal Article

of driver-response relationships: identifying factors using a novel framework integrating quantile regression

Journal Article

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Journal Article

Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

Journal Article

SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Journal Article

Presentation of regression analysis, GP and GMDH models to predict the pedestrian density in various

Iraj BARGEGOL; Seyed Mohsen HOSSEINIAN; Vahid NAJAFI MOGHADDAM GILANI; Mohammad NIKOOKAR; Alireza OROUEI

Journal Article