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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 is

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

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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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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: On 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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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 uncertain

Keywords： automated vehicles     platoon     distributed control     robustness    

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Global sensitivity analysis of certain and uncertain factors for a circular tunnel under seismic action

Nazim Abdul NARIMAN, Raja Rizwan HUSSAIN, Ilham Ibrahim MOHAMMAD, Peyman KARAMPOUR

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 6,   Pages 1289-1300 doi: 10.1007/s11709-019-0548-0

Abstract: There are many certain and uncertain design factors which have unrevealed rational effects on the generationIn this research paper, we have dedicated three certain and four uncertain design factors to quantify

Keywords： shear waves     Sobol’s sensitivity indices     maximum principal stress     maximum overall displacement     tensile damage    

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Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 488-497 doi: 10.1007/s11684-020-0762-0

Abstract: The artificial intelligence (AI) diagnosis model was constructed according to the dynamic uncertain causality

Keywords： knowledge representation     uncertain     causality     graphical model     artificial intelligence     diagnosis     dyspnea    

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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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Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

Ahmet SAYAR,Süleyman EKEN,Okan ÖZTÜRK

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 2,   Pages 98-108 doi: 10.1631/FITEE.1400165

Abstract: We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) parallelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. The key challenge is how to balance the spatial processing load across a large number of worker nodes, given significant performance heterogeneity in nodes and processing skews in the workload.

Keywords： Kd tree     Quad tree     Space partitioning     Spatial indexing     Range queries     Query optimization    

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

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 regression

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

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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

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

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

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

Global sensitivity analysis of certain and uncertain factors for a circular tunnel under seismic action

Nazim Abdul NARIMAN, Raja Rizwan HUSSAIN, Ilham Ibrahim MOHAMMAD, Peyman KARAMPOUR

Journal Article

Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

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

Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

Ahmet SAYAR,Süleyman EKEN,Okan ÖZTÜRK

Journal Article

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

Journal Article

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

Ali Reza GHANIZADEH, Morteza RAHROVAN

Journal Article