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Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang

Fan ZHANG, Mo LI, Shanshan GUO, Chenglong ZHANG, Ping GUO

Frontiers of Agricultural Science and Engineering 2018, Volume 5, Issue 2,   Pages 177-187 doi: 10.15302/J-FASE-2017177

Abstract: To improve the accuracy of runoff forecasting, an uncertain multiple linear regression (UMLR) model isthe developed system, and help decision makers to identify reasonable crop planting structure under multiple

Keywords： structure optimization     inexact two-stage stochastic programming     runoff forecasting     Shiyang River Basin     uncertainmultiple linear regression    

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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 regressionenables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiplelinear regression model is not feasible enough in this area because of nonlinear relationship between

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

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A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

Frontiers in Energy 2016, Volume 10, Issue 4,   Pages 459-465 doi: 10.1007/s11708-016-0424-8

Abstract: The multiple linear feedback regression model was applied to predict, with precision, the air conditioning

Keywords： commercial building     load prediction     multiple linear regression    

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Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

Juan WU, Jian ZHANG, Wenlin JIA, Huijun XIE, Bo ZHANG

Frontiers of Environmental Science & Engineering 2009, Volume 3, Issue 2,   Pages 241-247 doi: 10.1007/s11783-009-0023-6

Abstract: the chemical and physical water quality variables were studied by using principal component scores in multiplelinear regression analysis to predict N O flux.The multiple linear regression model against principal components indicated that different water parameters

Keywords： surface constructed wetland     nitrous oxide emission     water quality parameter     principal component analysis     multiplelinear regression    

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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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Estimation of photolysis half-lives of dyes in a continuous-flow system with the aid of quantitative structure-property relationship

Davoud BEIKNEJAD,Mohammad Javad CHAICHI

Frontiers of Environmental Science & Engineering 2014, Volume 8, Issue 5,   Pages 683-692 doi: 10.1007/s11783-014-0680-y

Abstract: study was carried out using 21 descriptors based on different chemometric tools including stepwise multiplelinear regression (MLR) and partial least squares (PLS) for the prediction of the photolysis half-life

Keywords： dye     photolysis half-life     quantitative structure-property relationship     continuous-flow     stepwise multiplelinear regression     partial least squares    

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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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Study of cold sky calibration and geophysical parameters retrieval for HY-2A satellite scanning microwave radiometer

Zhou Wu,Lin Mingsen,Li Yanmin,Wang Zhenzhan and Huang Lei

Strategic Study of CAE 2013, Volume 15, Issue 7,   Pages 75-80

Abstract: brightness temperature under different conditions of each frequency and polarization was calculated, and a linearregression model was established to fit different geophysical parameters retrieval coefficient, usingmultiple linear regression algorithm retrieving HY-2A microwave scanning radiometer geophysical parameters

Keywords： scanning microwave radiometer     multiple linear regression     multi satellites cross over     cold shy calibration    

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A novel approach for remanufacturing process planning considering uncertain and fuzzy information

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 3,   Pages 546-558 doi: 10.1007/s11465-021-0639-1

Abstract: comprehensively studied the interactions among damage conditions and quality requirements that involve uncertainHence, this challenge in the context of uncertain, fuzzy information is undertaken in this paper, and

Keywords： remanufacturing     uncertain and fuzzy information     process planning     T-S FNN    

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An uncertain energy planning model under carbon taxes

Hongkuan ZANG, Yi XU, Wei LI, Guohe HUANG, Dan LIU

Frontiers of Environmental Science & Engineering 2012, Volume 6, Issue 4,   Pages 549-558 doi: 10.1007/s11783-012-0414-y

Abstract: In this study, an interval fuzzy mixed-integer energy planning model (IFMI-EPM) is developed under considering the carbon tax policy. The developed IFMI-EPM incorporates techniques of interval-parameter programming, fuzzy planning and mixed-integer programming within a general energy planning model. The IFMI-EPM can not only be used for quantitatively analyzing a variety of policy scenarios that are associated with different levels of carbon tax policy, but also tackle uncertainties expressed as discrete intervals and fuzzy sets in energy and environment systems. Considering low, medium and high carbon tax rates, the model is applied to an ideal energy and environment system. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired carbon tax policy.

Keywords： energy     carbon tax     planning     uncertainty     fuzzy    

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Models of thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture

WEI Wenjian, DING Guoliang, HU Haitao, WANG Kaijian

Frontiers in Energy 2008, Volume 2, Issue 2,   Pages 227-234 doi: 10.1007/s11708-008-0020-7

Abstract: New models were developed by modifying the coefficients in existing correlations with multiple regression

Keywords： multiple regression     foundation     thermodynamic     influence     air-conditioning    

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Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing

Juan LIU, Fei QIAO, Yumin MA, Weichang KONG

Frontiers of Engineering Management 2018, Volume 5, Issue 4,   Pages 507-514 doi: 10.15302/J-FEM-2018045

Abstract: slack-based robust scheduling rule (SR) based on the analysis of robustness measurement for SMS with uncertain

Keywords： semiconductor manufacturing system     uncertain processing time     dynamic scheduling     slack-based robust scheduling    

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Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 498-505 doi: 10.1007/s11684-020-0791-8

Abstract: Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologiesOn the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosisapplied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain

Keywords： disorders of sex development (DSD)     intelligent diagnosis     dynamic uncertain causality graph    

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Presentation of machine learning methods to determine the most important factors affecting road traffic accidents on rural roads

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 5,   Pages 657-666 doi: 10.1007/s11709-022-0827-z

Abstract: Multiple Logistic Regression (MLR) was used to predict the likelihood of RTAs.

Keywords： safety     rural accidents     multiple logistic regression     artificial neural networks    

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cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain

Keqiang LI, Feng GAO, Shengbo Eben LI, Yang ZHENG, Hongbo GAO

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 3,   Pages 354-367 doi: 10.1007/s11465-018-0486-x

Abstract:

This study presents a distributed H-infinity control method for uncertain platoons with dimensionallymodel to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertainthe eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertainpart and a diagonally structured certain part by applying linear transformation.Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should

Keywords： automated vehicles     platoon     distributed control     robustness    

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Title Author Date Type Operation

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang

Fan ZHANG, Mo LI, Shanshan GUO, Chenglong ZHANG, Ping GUO

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

A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

Journal Article

Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

Juan WU, Jian ZHANG, Wenlin JIA, Huijun XIE, Bo ZHANG

Journal Article

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

Siyu ZHOU, Neng ZHU

Journal Article

Estimation of photolysis half-lives of dyes in a continuous-flow system with the aid of quantitative structure-property relationship

Davoud BEIKNEJAD,Mohammad Javad CHAICHI

Journal Article

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

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Journal Article

Study of cold sky calibration and geophysical parameters retrieval for HY-2A satellite scanning microwave radiometer

Zhou Wu,Lin Mingsen,Li Yanmin,Wang Zhenzhan and Huang Lei

Journal Article

A novel approach for remanufacturing process planning considering uncertain and fuzzy information

Journal Article

An uncertain energy planning model under carbon taxes

Hongkuan ZANG, Yi XU, Wei LI, Guohe HUANG, Dan LIU

Journal Article

Models of thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture

WEI Wenjian, DING Guoliang, HU Haitao, WANG Kaijian

Journal Article

Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing

Juan LIU, Fei QIAO, Yumin MA, Weichang KONG

Journal Article

Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

Journal Article

Presentation of machine learning methods to determine the most important factors affecting road traffic accidents on rural roads

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

Journal Article

cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain

Keqiang LI, Feng GAO, Shengbo Eben LI, Yang ZHENG, Hongbo GAO

Journal Article