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Predicting beach profile evolution with group method data handling-type neural networks on beaches with

M. A. LASHTEH NESHAEI, M. A. MEHRDAD, N. ABEDIMAHZOON, N. ASADOLLAHI

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 117-126 doi: 10.1007/s11709-013-0205-y

Abstract: present study, evolutionary algorithms (EAs) are employed for multi-objective Pareto optimum design of groupmethod data handling (GMDH)-type neural networks that have been used for bed evolution modeling in the

Keywords： beach profile evolution     genetic algorithms     group method of data handling     Pareto     reflective beaches    

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An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and groupmethod of data handling surrogate model

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 907-929 doi: 10.1007/s11709-020-0628-1

Abstract: Moreover, a modal property change vector is evaluated using the group method of data handling (GMDH)

Keywords： two-stage method     modal strain energy     surrogate model     GMDH     optimization damage detection    

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Lignin-based polymer with high phenolic hydroxyl group content prepared by the alkyl chain bridging method

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 8,   Pages 1075-1084 doi: 10.1007/s11705-022-2272-x

Abstract: Inspired by the importance of the phenolic group to the electron transporting property of hole transportmaterials, phenolic hydroxyl groups were introduced in lignosulfonate (LS) via the alkyl chain bridging methodThe results showed that the phenolic group was boosted from 0.81 mmol∙g–1 of LS to 1.19 mmolThe results indicate that the phenolic hydroxyl group of lignin can be easily boosted by the alkyl chainbridging method, and phenolated lignin-based polymers may have promising potential as dopants of PEDOT

Keywords： lignosulfonate     phenolic group     PEDOT:PLS     hole extract layer     energy level    

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Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems: An UncertaintyHandling Perspective Review

Li Sun, Fengqi You

Engineering 2021, Volume 7, Issue 9,   Pages 1239-1247 doi: 10.1016/j.eng.2021.04.020

Abstract: The burgeoning era of machine learning (ML) and data-driven control (DDC) techniques promises an improved

Keywords： Smart power generation     Machine learning     Data-driven control     Systems engineering    

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Anensemble method for data stream classification in the presence of concept drift

Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1059-1068 doi: 10.1631/FITEE.1400398

Abstract: , and data concept drift; these features differentiate the data stream from standard types of data.An issue for the data stream is classification of input data.In addition, a new method is used to determine drift, which emphasizes the precision of the algorithmAnother characteristic of the proposed method is removal of different numbers of the base classifiersFurthermore, the proposed method is tested on a set of standard data and the results confirm higher accuracy

Keywords： Data stream     Classificaion     Ensemble classifiers     Concept drift    

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Prediction of the flash points of alkanes by group bond contribution method using artificial neural networks

PAN Yong, JIANG Juncheng, WANG Zhirong

Frontiers of Chemical Science and Engineering 2007, Volume 1, Issue 4,   Pages 390-394 doi: 10.1007/s11705-007-0071-z

Abstract: A group bond contribution model using artificial neural networks, which had the high ability of nonlinearThis model contained not only the information of group property but also connectivity in molecules.A set of 16 group bonds were used as input parameters of neural networks to study the correlation ofThe results showed that the predicted flash points were in good agreement with the experimental dataThe method can be used not only to reveal the quantitative correlation between flash points and molecular

Keywords： information     nonlinear     quantitative correlation     superior     molecular    

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Numerical evaluation of group-pile foundation subjected to cyclic horizontal load

Youngji JIN, Xiaohua BAO, Yoshimitsu KONDO, Feng ZHANG,

Frontiers of Structural and Civil Engineering 2010, Volume 4, Issue 2,   Pages 196-207 doi: 10.1007/s11709-010-0021-6

Abstract: In this paper, three-dimensional (3D) finite element analyses of a real-scale group-pile foundation subjectedIn order to consider the influence of an effective stress path on the prediction of the group-pile foundation, the analyses are conducted within the framework of the soil-water coupling method with finite-differenceThe applicability of the proposed numerical method is encouraging, and therefore, it is quite confidentto say that the method can be used to predict the mechanical behaviors of group-pile foundation to a

Keywords： group-pile foundation     real-scale cyclic loading test     three-dimensional finite element method (3D-FEM)    

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Group-based multiple pipe routing method for aero-engine focusing on parallel layout

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 798-813 doi: 10.1007/s11465-021-0645-3

Abstract: This paper presents an automatic multiple pipe routing method for aero-engine that focuses on parallelBy using this algorithm, pipes in the same group share the layout space information with one another,and the optimal layout solution of pipes in this group can be obtained in the same evolutionary progressparallel pipes that would cause assembly stress in actual assembly, an accurate parallelization processing methodsimulation results on an aero-engine demonstrate the feasibility and effectiveness of the proposed method

Keywords： multiple pipe routing     optimization algorithm     aero-engine     pipe grouping     parallel layout    

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Module-based method for design and analysis of reconfigurable parallel robots

Fengfeng XI, Yuwen LI, Hongbo WANG

Frontiers of Mechanical Engineering 2011, Volume 6, Issue 2,   Pages 151-159 doi: 10.1007/s11465-011-0121-6

Abstract:

This paper presents a method for the design and analysis of reconfigurable parallel robots.Among three types of reconfigurations, namely, geometry morphing, topology morphing, and group morphing, the method presented here is for the last two reconfigurations, thereby advancing the current researchIt is shown that the module-based method not only provides a systematic way of designing a reconfigurableTwo examples are provided, one showing the topology morphing and the other showing the group morphing

Keywords： reconfigurable parallel robot     topology morphing     group morphing    

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Handling Stability for Four-wheel Steering Vehicle Based on μ Synthesis Robust Control

Yin Guodong,Chen Nan,Li Pu

Strategic Study of CAE 2005, Volume 7, Issue 4,   Pages 54-58

Abstract:

The vehicles always undertake different loadings including external disturbances and the design of vehicle control system has model errors. The primary design techniques for 4WS controller are their inability to degrade the performance of closed-loop systems. The design of yaw rate tracking control system architecture by using μ synthesis robust control is presented and the weighting functions are selected. The results show that the control system has fine dynamic characteristic, robust stability and robust performance, and the 4WS vehicle with the proposed control strategy can provide greater maneuverability and driving safety.

Keywords： four-wheel steering     robust control     handling stability     μ synthesis    

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An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings

Yanfeng PENG, Junsheng CHENG, Yanfei LIU, Xuejun LI, Zhihua PENG

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 301-310 doi: 10.1007/s11465-017-0449-7

Abstract:

A novel data-driven method based on Gaussian mixture model (GMM) and distance evaluation techniqueThe data sets are clustered by GMM to divide all data sets into several health states adaptively andtraining data sets.sets into several health states and remove the abnormal data sets.Experimental results indicate that the proposed method reliably predicts the RUL of rolling bearings.

Keywords： Gaussian mixture model     distance evaluation technique     health state     remaining useful life     rolling bearing    

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A review of intelligent optimization for group scheduling problems in cellular manufacturing

Frontiers of Engineering Management   Pages 406-426 doi: 10.1007/s42524-022-0242-0

Abstract: Given that group technology can reduce the changeover time of equipment, broaden the productivity, andenhance the flexibility of manufacturing, especially cellular manufacturing, group scheduling problemsproduction cells in view of major setup times between groups and the other is how to schedule jobs in each groupoutlooks are given for outspread problems and problem algorithms for future research in the fields of group

Keywords： cellular manufacturing     group scheduling     flowshop     literature review    

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Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 882-895 doi: 10.1007/s11709-022-0859-4

Abstract: The Limit Equilibrium Method (LEM) is commonly used in traditional slope stability analyses, but it isA CNN model can process data quickly and complete a large amount of data analysis in a specific situationIt is difficult to get enough slope data samples in practical engineering.This study proposes a slope database generation method based on the LEM.In particular, the combination of typical actual slopes and generated slope data provides enough training

Keywords： slope stability     limit equilibrium method     convolutional neural network     database for slopes     big data    

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Conception and Exploration of Using Data as a Service in Tunnel Construction with the NATM Article

Bowen Du, Yanliang Du, Fei Xu, Peng He

Engineering 2018, Volume 4, Issue 1,   Pages 123-130 doi: 10.1016/j.eng.2017.07.002

Abstract:

The New Austrian Tunneling Method (NATM) has been widely used in the construction of mountain tunnelsThe variation patterns of advance geological prediction data, stress–strain data of supportingIn order to solve this problem, a novel data service system is proposed that uses data-association technologyand the NATM, with the support of a big data environment.These data associations and relations are then stored in a data pool.

Keywords： New Austrian Tunneling Method     Big data environments     Data as a service     Tunnel construction    

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Emergence mechanisms of group consensus in social networks

Frontiers of Engineering Management doi: 10.1007/s42524-023-0277-x

Abstract: This article redefines group consensus as the emergence of collective intelligence resulting from self-organizingactions and interactions of individuals within a social network group.In our exploration of extant research on group consensus, we illuminate two frequently underestimatedThis process encompasses self-organized communication and interaction among group members, collectivelyguiding the group towards cognitive convergence and viewpoint integration.

Keywords： group consensus     social network     collective intelligence    

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Title Author Date Type Operation

Predicting beach profile evolution with group method data handling-type neural networks on beaches with

M. A. LASHTEH NESHAEI, M. A. MEHRDAD, N. ABEDIMAHZOON, N. ASADOLLAHI

Journal Article

An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and groupmethod of data handling surrogate model

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Journal Article

Lignin-based polymer with high phenolic hydroxyl group content prepared by the alkyl chain bridging method

Journal Article

Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems: An UncertaintyHandling Perspective

Li Sun, Fengqi You

Journal Article

Anensemble method for data stream classification in the presence of concept drift

Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI

Journal Article

Prediction of the flash points of alkanes by group bond contribution method using artificial neural networks

PAN Yong, JIANG Juncheng, WANG Zhirong

Journal Article

Numerical evaluation of group-pile foundation subjected to cyclic horizontal load

Youngji JIN, Xiaohua BAO, Yoshimitsu KONDO, Feng ZHANG,

Journal Article

Group-based multiple pipe routing method for aero-engine focusing on parallel layout

Journal Article

Module-based method for design and analysis of reconfigurable parallel robots

Fengfeng XI, Yuwen LI, Hongbo WANG

Journal Article

Handling Stability for Four-wheel Steering Vehicle Based on μ Synthesis Robust Control

Yin Guodong,Chen Nan,Li Pu

Journal Article

An adaptive data-driven method for accurate prediction of remaining useful life of rolling bearings

Yanfeng PENG, Junsheng CHENG, Yanfei LIU, Xuejun LI, Zhihua PENG

Journal Article

A review of intelligent optimization for group scheduling problems in cellular manufacturing

Journal Article

Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Journal Article

Conception and Exploration of Using Data as a Service in Tunnel Construction with the NATM

Bowen Du, Yanliang Du, Fei Xu, Peng He

Journal Article

Emergence mechanisms of group consensus in social networks

Journal Article