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E-commerce businessmodel mining and prediction

Zhou-zhou HE,Zhong-fei ZHANG,Chun-ming CHEN,Zheng-gang WANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 9,   Pages 707-719 doi: 10.1631/FITEE.1500148

Abstract: We study the problem of business model mining and prediction in the e-commerce context.Taking this observation into consideration, we propose a new method for e-commerce business model miningand prediction, called EBMM, which combines regression with community analysis.e-commerce data demonstrate the promise and superiority of EBMM to the state-of-the-art methods in terms of businessmodel mining and prediction.

Keywords： E-commerce     Business model prediction     Consumer influence     Social network     Sales prediction    

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Energy storage resources management: Planning, operation, and business model

Frontiers of Engineering Management   Pages 373-391 doi: 10.1007/s42524-022-0194-4

Abstract: study presents a comprehensive review of managing ESS from the perspectives of planning, operation, and businessmodel.Finally, it discusses the business models of ESS.Traditional business models involve ancillary services and load transfer, while emerging business models

Keywords： storage system     energy storage resources management     planning configuration     operational management     businessmodel    

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Research on New Mode and Business Model of Manufacturing Led by New-Generation Artificial Intelligence

Research Group for Research on New Mode and Business Model of Manufacturing Led by New-Generation Artificial

Strategic Study of CAE 2018, Volume 20, Issue 4,   Pages 66-72 doi: 10.15302/J-SSCAE-2018.04.011

Abstract: industry are facing major changes, which also provides opportunities for formation of new modes and businessDriven by the new generation of artificial intelligence technology, new modes and business models generatedanalyzed the development trends, typical types, and key platform technologies of the new modes and businessmanufacturing, and proposed the development guidelines, goals, and approaches for the new modes and businessas examples, and put forward the development directions, goals, and policy suggestions for the two business

Keywords： artificial intelligence     manufacturing     new mode     new business model    

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fractureA total of 147 raw input features are considered in our model.The presented model is compared with several benchmarks based on various metrics to prove its effectiveness

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

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Research on the business model innovation of wind power equipment manufacturing industry in China based

Hu Xuhua, ,,Shi Fangyan and Xu Junjie

Strategic Study of CAE 2015, Volume 17, Issue 3,   Pages 88-95

Abstract: And the strategic pattern of business model is discussed based on PEST analysis .The concept of businessmodel innovation design includes segment type， contraction type， integration type and extended type.Finally， the suggestions are put forward to guarantee the business model innovation of wind power equipment

Keywords： wind power equipment manufacturing industry； business model innovation； industrial chain；PEST analysis    

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Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 1,   Pages 72-82 doi: 10.1007/s11709-013-0185-y

Abstract: A support vector machine (SVM) model has been developed for the prediction of liquefaction susceptibilityThis paper examines the potential of SVM model in prediction of liquefaction using actual field coneUsing cone resistance ( ) and cyclic stress ratio ( ), model has been developed for prediction of liquefactionhorizontal acceleration ), for prediction of liquefaction.model predicts with accuracy of 89%.

Keywords： earthquake     cone penetration test     liquefaction     support vector machine (SVM)     prediction    

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A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 7, doi: 10.1007/s11783-023-1688-y

Abstract:

● A novel VMD-IGOA-LSTM model has proposed for the prediction of

Keywords： Water quality prediction     Grasshopper optimization algorithm     Variational mode decomposition     Long short-term    

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Improved analytical model for residual stress prediction in orthogonal cutting

Zhaoxu QI,Bin LI,Liangshan XIONG

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 3,   Pages 249-256 doi: 10.1007/s11465-014-0310-1

Abstract: for residual stress prediction in orthogonal cutting.In application of the model, a problem of low precision of the surface residual stress prediction isThese shortages may directly lead to the low precision of the surface residual stress prediction.To eliminate these shortages and make the prediction more accurate, an improved model is proposed.Also, Jiann’s model and the improved model are simulated under the same conditions with cutting

Keywords： residual stress     analytical model     orthogonal cutting     cutting force     cutting temperature    

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Fracture model for the prediction of the electrical percolation threshold in CNTs/Polymer composites

Yang SHEN, Pengfei HE, Xiaoying ZHUANG

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 1,   Pages 125-136 doi: 10.1007/s11709-017-0396-8

Abstract: In this paper, we propose a 3D stochastic model to predict the percolation threshold and the effectiveWe consider the tunneling effect in our model so that the unrealistic interpenetration can be avoided

Keywords： electrical percolation     CNTs/Polymer composites     fracture model     electric conductivity     tunnelling effects    

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Performance prediction of switched reluctance generator with time average and small signal models

Jyoti KOUJALAGI, B. UMAMAHESWARI, R. ARUMUGAM

Frontiers in Energy 2013, Volume 7, Issue 1,   Pages 56-68 doi: 10.1007/s11708-012-0216-8

Abstract: This paper presents the complete mathematical model and predicts the performance of switched reluctanceThe complete mathematical model is developed in three stages.First, a switching model is developed based on quasi-linear inductance profile.Finally, to track control voltage and current wave shapes, a small signal model is designed.The effectiveness of the complete multilevel model combining electrical machine, power converter, load

Keywords： generator     reluctance     switching model     small signal model     time average model    

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Pathway to energy technical innovation and commercialization based on Internet plus DES

Huiping LIU

Frontiers in Energy 2016, Volume 10, Issue 1,   Pages 65-78 doi: 10.1007/s11708-015-0391-5

Abstract: were proposed. 4E elements should be used to evaluate and choose the project and lead the innovation model

Keywords： “Internet Plus”     distributed energy system (DES)     business model     technical innovation     commercialization    

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Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 8,   Pages 976-989 doi: 10.1007/s11709-022-0840-2

Abstract: This paper improves ANN training after introducing BOA as a hybrid model (BOA-ANN).

Keywords： damage prediction     ANN     BOA     FEM     experimental modal analysis    

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Prediction method of foundation vibration responses induced by impact loading using modified andersonmodel

Fang Bo

Strategic Study of CAE 2014, Volume 16, Issue 11,   Pages 96-102

Abstract:

A synthetic method, which combines theoretical model and field measurementThe Anderson model was modified and verified by the data measured in field hammer impact tests.Then the impact induced vibration was predicted using the modified Anderson model.Finally, the prediction results were compared with the measured results.The results indicates that the prediction results approximately approach to the measured results.

Keywords： prediction method     impact loading     vibration effects     anderson model    

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Enterprise-level business component identificationin business architecture integration Article

Jiong FU, Xue-shan LUO, Ai-min LUO, Jun-xian LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 9,   Pages 1320-1335 doi: 10.1631/FITEE.1601836

Abstract: The component-based business architecture integration of militaryinformation systems is a popular researchIdentifying enterprise-level business componentsis an important issue in business architecture integrationCurrentlyused methodologies for business component identification tend to focuson software-level business, approaches to enterprise-level business component identificationhave proven laborious.componentsbased on the component business model and the Department of DefenseArchitecture Framework

Keywords： Business architecture integration     Business component     Component identification     Create     read     update    

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A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0688-0

Abstract: In this study, we develop a predictive model of the dimensional accuracy for precision milling of thin-walledBased on the experimental data collected during the milling experiments, the proposed model proved toThe average classification accuracy obtained using the proposed deep learning model was 9.55% higherHence, the proposed hybrid model provides an efficient way of fusing different sources of process dataand can be adopted for prediction of the machining quality in noisy environments.

Keywords： precision milling     dimensional accuracy     cutting force     convolutional neural networks     coherent noise    

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Title Author Date Type Operation

E-commerce businessmodel mining and prediction

Zhou-zhou HE,Zhong-fei ZHANG,Chun-ming CHEN,Zheng-gang WANG

Journal Article

Energy storage resources management: Planning, operation, and business model

Journal Article

Research on New Mode and Business Model of Manufacturing Led by New-Generation Artificial Intelligence

Research Group for Research on New Mode and Business Model of Manufacturing Led by New-Generation Artificial

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Research on the business model innovation of wind power equipment manufacturing industry in China based

Hu Xuhua, ,,Shi Fangyan and Xu Junjie

Journal Article

Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

Journal Article

A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

Journal Article

Improved analytical model for residual stress prediction in orthogonal cutting

Zhaoxu QI,Bin LI,Liangshan XIONG

Journal Article

Fracture model for the prediction of the electrical percolation threshold in CNTs/Polymer composites

Yang SHEN, Pengfei HE, Xiaoying ZHUANG

Journal Article

Performance prediction of switched reluctance generator with time average and small signal models

Jyoti KOUJALAGI, B. UMAMAHESWARI, R. ARUMUGAM

Journal Article

Pathway to energy technical innovation and commercialization based on Internet plus DES

Huiping LIU

Journal Article

Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

Journal Article

Prediction method of foundation vibration responses induced by impact loading using modified andersonmodel

Fang Bo

Journal Article

Enterprise-level business component identificationin business architecture integration

Jiong FU, Xue-shan LUO, Ai-min LUO, Jun-xian LIU

Journal Article

A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of

Journal Article