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A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Basedon Multi-Factor Analysis and a Multi-Model Ensemble Article

Hui Liu, Rui Yang, Zhu Duan, Haiping Wu

Engineering 2021, Volume 7, Issue 12,   Pages 1751-1765 doi: 10.1016/j.eng.2020.10.023

Abstract: In this paper, a new DO hybrid forecasting model is proposed that includes three stages: multi-factorThe consideration of multiple factors makes model fusion more effective.Finally, a multi-factor ensemble model for DO is obtained by weighted allocation.The performance of the proposed model is verified by time-series data collected by the pacific islands② the proposed model is superior to other comparison models; and ③ the forecasting model can be used

Keywords： Dissolved oxygen concentrations forecasting     Time-series multi-step forecasting     Multi-factor analysis     Empirical wavelet transform decomposition     Multi-model optimization ensemble    

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Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target Research Articles

Weihua Wu, Yichao Cai, Hongbin Jin, Mao Zheng, Xun Feng, Zewen Guan,weihuawu1987@163.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 1,   Pages 1-140 doi: 10.1631/FITEE.2000105

Abstract: By defining a new generalized labeled multi-Bernoulli density, we prove that it is closed under the Chapman-Kolmogorov

Keywords： Multi-maneuvering-target tracking     Multi-model     Generalized labeled multi-Bernoulli filter     Multi-target    

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Multi-model ensemble deep learning method for intelligent fault diagnosis with high-dimensional samples

Xin ZHANG, Tao HUANG, Bo WU, Youmin HU, Shuai HUANG, Quan ZHOU, Xi ZHANG

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 2,   Pages 340-352 doi: 10.1007/s11465-021-0629-3

Abstract: Therefore, a multi-model ensemble deep learning method based on deep convolutional neural network (DCNNLastly, a 2D DCNN model with multi-layer convolution and pooling is used to automatically learn features

Keywords： fault intelligent diagnosis     deep learning     deep convolutional neural network     high-dimensional samples    

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Evaluation of the impact of multi-source uncertainties on meteorological and hydrological ensemble forecasting Article

Zhangkang Shu, Jianyun Zhang, Lin Wang, Junliang Jin, Ningbo Cui, Guoqing Wang, Zhouliang Sun, Yanli Liu, Zhenxin Bao, Cuishan Liu

Engineering 2023, Volume 24, Issue 5,   Pages 213-229 doi: 10.1016/j.eng.2022.06.007

Abstract:

Evaluating the impact of multi-source uncertainties in complex forecasting systems is essential toIn this study, we developed a general ensemble framework based on Bayesian model averaging (BMA) forevaluating the impact of multi-source uncertainties in complex forecast systems.The hydrological model structure uncertainty was more prominent than the parameter uncertainty.The developed multi-source uncertainty assessment framework improves our understanding of the complex

Keywords： Meteorological and hydrological forecasting     Uncertainty estimation     Bayesian model averaging     Ensembleprediction     Multi-model    

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Development of machine learning multi-city model for municipal solid waste generation prediction

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 9, doi: 10.1007/s11783-022-1551-6

Abstract:

● A database of municipal solid waste (MSW) generation in China was established.

Keywords： Municipal solid waste     Machine learning     Multi-cities     Gradient boost regression tree    

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A practical multi-lane factor model of bridges based on multi-truck presence considering lane load disparities

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 4,   Pages 877-894 doi: 10.1007/s11709-021-0756-2

Abstract: Many bridge design specifications consider multi-lane factors (MLFs) a critical component of the trafficload model.Measured multi-lane traffic data generally exhibit significant lane disparities in traffic loads overTo address this drawback, a multi-coefficient MLF model was developed based on an improved probabilisticThe proposed MLF model and approach were calibrated and demonstrated through an example site.

Keywords： bridges     multi-lane factor     traffic load     lane load disparity     multi-truck presence     weigh-in-motion    

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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0736-9

Abstract: Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studiedSecond, the localization for multi-source faults is seldom investigated, although locating the anomalyweaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensorFirst, an MSR model is developed to learn MSRs automatically and further obtain fault recognition resultsSecond, centrality measures are employed to analyze the MSR graphs learned by the MSR model, and fault

Keywords： fault recognition     fault localization     multi-sensor relations     network analysis     graph neural network    

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Hydromechanical model for hydraulic fractures using XFEM

Bo HE

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 240-249 doi: 10.1007/s11709-018-0490-6

Abstract: In this study, a hydromechanical model for fluid flow in fractured porous media is presented.Furthermore, the model is extended to includes crack propagation.examples are presented to demonstrate the versatility and efficiency of this two-scale hydromechanical model

Keywords： multi-phase medium     porous     fracture     multi-scale method    

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Applying the multi-zone model in predicting the operating range of HCCI engines

Ming JIA, Maozhao XIE, Zhijun PENG,

Frontiers in Energy 2010, Volume 4, Issue 3,   Pages 414-423 doi: 10.1007/s11708-010-0108-8

Abstract: In this paper, a multi-zone model is developed to predict the operating range of homogeneous charge compressionsimulating an HCCI engine fueled with iso-octane, the knock and cycle-to-cycle variations predicted by the modeldifferent initial temperatures and equivalence ratios; the operating range was also well reproduced by the modelFurthermore, the model was applied to predict the operating range of the HCCI engine under different

Keywords： homogeneous charge compression ignition (HCCI) engine     multi-zone     operating range    

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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

Frontiers in Energy doi: 10.1007/s11708-023-0912-6

Abstract: In this paper, a multi-timescale optimal scheduling model is established for interconnected data centers(IDCs) based on model predictive control (MPC), including day-ahead optimization, intraday rolling optimizationaims at the lowest power fluctuation, eliminating the impact of prediction errors through coordinated multi-timescale

Keywords： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed    

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A multi-scale model for CO

G. X. WANG, X. R. WEI, V. RUDOLPH, C. T. WEI, Y. QIN

Frontiers of Chemical Science and Engineering 2009, Volume 3, Issue 1,   Pages 20-25 doi: 10.1007/s11705-009-0138-0

Abstract: This paper presents a multi-scale model to simulate the multicomponent gas diffusion and flow in bulkThe model is developed based on a bi-dispersed structure model by assuming that coal consists of microporousThe bi-disperse diffusion theory and the Maxwell-Stefan approach were incorporated in the model, providingIn the model, the counter diffusion process is numerically coupled with the flow of the mixture gasesThe model was validated by both experimental data from literature and our CO flush tests, and shows

Keywords： multi-scale model     gas transport     coal     coalbed methane     CO2 sequestration    

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Cutting CO emissions through demand side regulation: Implications from multi-regional input–output linearprogramming model

Frontiers of Engineering Management   Pages 452-461 doi: 10.1007/s42524-022-0209-1

Abstract: This study combines multi-regional input–output (MRIO) model with linear programming (LP) model to exploreThe proposed MRIO–LP model considers the inter-relationship among various sectors and

Keywords： CO2 emissions     demand side regulation     multi-regional input–output model     linear programmingmodel    

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Hydraulic model for multi-sources reclaimed water pipe network based on EPANET and its applications in

JIA Haifeng, WEI Wei, XIN Kunlun

Frontiers of Environmental Science & Engineering 2008, Volume 2, Issue 1,   Pages 57-62 doi: 10.1007/s11783-008-0013-0

Abstract: reclaimed water soundly, Beijing planned to build a large scale reclaimed water pipe networks with multi-sourcesIn order to support the plan, the integrated hydraulic model of planning pipe network was developed based

Keywords： diameter     Beijing municipal     reclaimed     planning     elevation    

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Mechanical responses of multi-layered ground due to shallow tunneling with arbitrary ground surface load

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 5,   Pages 745-762 doi: 10.1007/s11709-023-0935-4

Abstract: An analytical model based on complex variable theory is proposed to investigate ground responses dueto shallow tunneling in multi-layered ground with an arbitrary ground surface load.To solve the proposed multi-boundary problem, a series of analytic functions is introduced to accuratelyBased on the principle of linear-elastic superposition, the multi-boundary problem is converted intoThe present model is superior to the classical model for analyzing ground responses of shallow tunneling

Keywords： analytical model     mechanical response     multi-layered ground     shallow tunneling     ground surface load    

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Contact detection with multi-information fusion for quadruped robot locomotion under unstructured terrain

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 3, doi: 10.1007/s11465-023-0760-4

Abstract: of contact detection for quadruped robots, a detection approach based on the probabilistic contact modelwith multi-information fusion is presented to detect the actual contact states of robotic feet withThe overall contact states are obtained by the classification of the model-based predicted probabilitiesThe probabilistic model parameters are determined by testing on the single-leg experimental platform.

Keywords： multi-information fusion     contact detection     quadruped robot     probabilistic contact model     unstructured    

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Title Author Date Type Operation

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Basedon Multi-Factor Analysis and a Multi-Model Ensemble

Hui Liu, Rui Yang, Zhu Duan, Haiping Wu

Journal Article

Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target

Weihua Wu, Yichao Cai, Hongbin Jin, Mao Zheng, Xun Feng, Zewen Guan,weihuawu1987@163.com

Journal Article

Multi-model ensemble deep learning method for intelligent fault diagnosis with high-dimensional samples

Xin ZHANG, Tao HUANG, Bo WU, Youmin HU, Shuai HUANG, Quan ZHOU, Xi ZHANG

Journal Article

Evaluation of the impact of multi-source uncertainties on meteorological and hydrological ensemble forecasting

Zhangkang Shu, Jianyun Zhang, Lin Wang, Junliang Jin, Ningbo Cui, Guoqing Wang, Zhouliang Sun, Yanli Liu, Zhenxin Bao, Cuishan Liu

Journal Article

Development of machine learning multi-city model for municipal solid waste generation prediction

Journal Article

A practical multi-lane factor model of bridges based on multi-truck presence considering lane load disparities

Journal Article

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Journal Article

Hydromechanical model for hydraulic fractures using XFEM

Bo HE

Journal Article

Applying the multi-zone model in predicting the operating range of HCCI engines

Ming JIA, Maozhao XIE, Zhijun PENG,

Journal Article

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

Journal Article

A multi-scale model for CO

G. X. WANG, X. R. WEI, V. RUDOLPH, C. T. WEI, Y. QIN

Journal Article

Cutting CO emissions through demand side regulation: Implications from multi-regional input–output linearprogramming model

Journal Article

Hydraulic model for multi-sources reclaimed water pipe network based on EPANET and its applications in

JIA Haifeng, WEI Wei, XIN Kunlun

Journal Article

Mechanical responses of multi-layered ground due to shallow tunneling with arbitrary ground surface load

Journal Article

Contact detection with multi-information fusion for quadruped robot locomotion under unstructured terrain

Journal Article