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Timing decision-making method of engine blades for predecisional remanufacturing based on reliability analysis

Le CHEN, Xianlin WANG, Hua ZHANG, Xugang ZHANG, Binbin DAN

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 4,   Pages 412-421 doi: 10.1007/s11465-019-0551-0

Abstract: predicted by using the characteristic values of performance degradation of products combined with the leastsquares support vector regression algorithm.

Keywords： predecisional remanufacturing     reliability     least squares support vector regression (LS-SVR)     game theory    

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Identification of thermal error in a feed system based on multi-class LS-SVM

Chao JIN, Bo WU, Youmin HU, Yao CHENG

Frontiers of Mechanical Engineering 2012, Volume 7, Issue 1,   Pages 47-54 doi: 10.1007/s11465-012-0307-6

Abstract: Using multi-class least squares support vector machines (LS-SVM), the thermal positioning error of thevariance and mean square value of the temperatures of supporting bearings and screw-nut as feature vector

Keywords： least squares support vector machine (LS-SVM)     feed system     thermal error     precision machining    

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Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric characteristics

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 474-485 doi: 10.1631/FITEE.1400295

Abstract: In this work, principal component analysis (PCA) is fused with forward stepwise regression (SWR), artificialneural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the least squares support vectormachine (LS-SVM) model for the prediction of BP reactivity to an unsupported back in normotensive andperformance of the constructed models, using appropriate statistical indices, shows clearly that a PCA-based LS-SVM(PCA-LS-SVM) model is a promising approach for the prediction of BP reactivity in comparison to others

Keywords： Blood pressure (BP)     Principal component analysis (PCA)     Forward stepwise regression     Artificial neuralnetwork (ANN)     Adaptive neuro-fuzzy inference system (ANFIS)     Least squares support vector machine (LS-SVM)    

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Prediction of vibration response of powerhouse structures based on LS-SVM optimized by PSO

Lian Jijian,He Longjun,Wang Haijun

Strategic Study of CAE 2011, Volume 13, Issue 12,   Pages 45-50

Abstract: and powerhouse,and then the vibration response forecasting model of the powerhouse is built based on LS-SVM

Keywords： powerhouse     coupled vibration     particle swarm optimization algorithm     least squares support vector machines    

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Generalization and application in time series forecasting of the least square support vector machine

Xiang Xiaodong

Strategic Study of CAE 2008, Volume 10, Issue 11,   Pages 89-92

Abstract: more future information than historical data in time-series,the paper extends the prediction method of leastsquare support vector machine and obtains a more general prediction model of least square support vectorthat the extended model is more effective.Therefore it improves the value of the prediction method of leastsquare support vector machine.

Keywords： least square support vector machine     generalization     time series     forecasting    

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Unconfined compressive strength prediction of soils stabilized using artificial neural networks and supportvector machines

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 520-536 doi: 10.1007/s11709-021-0689-9

Abstract: Two artificial-intelligence-based models including artificial neural networks and support vector machinesThis study demonstrates the better performance of support vector machines in predicting the strengthThe type of kernel function used in support vector machine models contributed positively to the performance

Keywords： unconfined compressive strength     artificial neural network     support vector machine     predictive models     regression    

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Interactive image segmentation with a regression based ensemble learning paradigm Article

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 1002-1020 doi: 10.1631/FITEE.1601401

Abstract: This paper presents a novel interactive image segmentation method via a regression-based ensemble modelFirst, two spline regressors with a complementary nature are constructed based on multivariate adaptive regressionsplines (MARS) and smooth thin plate spline regression (TPSR).Next, a support vector regression (SVR) based decision fusion model is adopted to integrate the resultsFinally, the GraphCut is introduced and combined with the SVR ensemble results to achieve image segmentation

Keywords： Interactive image segmentation     Multivariate adaptive regression splines (MARS)     Ensemble learning     Thin-platespline regression (TPSR)     Semi-supervised learning     Support vector regression (SVR)    

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LSSVM-based approach for refining soil failure criteria and calculating safety factor of slopes

Shiguo XIAO; Shaohong LI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 871-881 doi: 10.1007/s11709-022-0863-8

Abstract: In the work reported here, an analysis method based on the least square support vector machine (LSSVM

Keywords： slope stability     safety factor     failure criterion     least square support vector machine    

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electroencephalogram signals using spatial constraint independent component analysis based recursive leastsquares in brain-computer interface

Bang-hua YANG,Liang-fei HE,Lin LIN,Qian WANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 486-496 doi: 10.1631/FITEE.1400299

Abstract: interfaces (BCIs), a method named spatial constraint independent component analysis based recursive leastsquares (SCICA-RLS) is proposed.

Keywords： Brain-computer interface (BCI)     Spatial constraint independent component analysis based recursive leastsquares (SCICA-RLS)    

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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 susceptibilityThe effect of capacity factor ( ) on number of support vector and model accuracy has also been investigated

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

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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: carried out using 21 descriptors based on different chemometric tools including stepwise multiple linear regression(MLR) and partial least squares (PLS) for the prediction of the photolysis half-life ( ) of dyes.

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

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artificial intelligence based method for evaluating power grid node importance using network embedding and supportvector regression Research Papers

Hui-fang WANG, Chen-yu ZHANG, Dong-yang LIN, Ben-teng HE

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 6,   Pages 816-828 doi: 10.1631/FITEE.1800146

Abstract: Finally, a support vector regression model is trained based on the optimized sample set for the later

Keywords： Power grid     Artificial intelligence     Node importance     Text-associated DeepWalk     Network embedding     Supportvector regression    

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Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and supportvector machine

Ali Reza GHANIZADEH, Hakime ABBASLOU, Amir Tavana AMLASHI, Pourya ALIDOUST

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 215-239 doi: 10.1007/s11709-018-0489-z

Abstract: paper aims to explore two machine learning algorithms including artificial neural network (ANN) and supportvector machine (SVM) to predict the compressive strength of bentonite/sepiolite plastic concretes.

Keywords： bentonite/sepiolite plastic concrete     compressive strength     artificial neural network     support vector machine    

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Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA None

Xin CHEN, Ding WANG, Rui-rui LIU, Jie-xin YIN, Ying WU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 7,   Pages 917-936 doi: 10.1631/FITEE.1700735

Abstract: Based on this, a structural total least squares (STLS) optimization model is developed and the inversethat the theoretical performance of the STLS method is consistent with that of the constrained total leastsquares method under first-order error analysis, both of which can achieve the Cramér-Rao lower bound

Keywords： Single-station     Structural total least squares     Inverse iteration     Angle-of-arrival (AOA)     Time-of-arrival    

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Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

Frontiers of Environmental Science & Engineering 2019, Volume 13, Issue 2, doi: 10.1007/s11783-019-1102-y

Abstract:

An image-recognition-based diagnosis system of pipe defect types was established.

1043 practical pipe images were gathered by CCTV robot in a southern Chinese city.

The overall accuracy of the system is 84% and the highest accuracy is 99.3%.

The accuracy shows positive correlation to the number of training samples.

Keywords： Sewer pipe defects     Defect diagnosing     Image recognition     Multi-features extraction     Support vector machine    

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Title Author Date Type Operation

Timing decision-making method of engine blades for predecisional remanufacturing based on reliability analysis

Le CHEN, Xianlin WANG, Hua ZHANG, Xugang ZHANG, Binbin DAN

Journal Article

Identification of thermal error in a feed system based on multi-class LS-SVM

Chao JIN, Bo WU, Youmin HU, Yao CHENG

Journal Article

Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric characteristics

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

Journal Article

Prediction of vibration response of powerhouse structures based on LS-SVM optimized by PSO

Lian Jijian,He Longjun,Wang Haijun

Journal Article

Generalization and application in time series forecasting of the least square support vector machine

Xiang Xiaodong

Journal Article

Unconfined compressive strength prediction of soils stabilized using artificial neural networks and supportvector machines

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

Journal Article

Interactive image segmentation with a regression based ensemble learning paradigm

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Journal Article

LSSVM-based approach for refining soil failure criteria and calculating safety factor of slopes

Shiguo XIAO; Shaohong LI

Journal Article

electroencephalogram signals using spatial constraint independent component analysis based recursive leastsquares in brain-computer interface

Bang-hua YANG,Liang-fei HE,Lin LIN,Qian WANG

Journal Article

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

Pijush SAMUI

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

artificial intelligence based method for evaluating power grid node importance using network embedding and supportvector regression

Hui-fang WANG, Chen-yu ZHANG, Dong-yang LIN, Ben-teng HE

Journal Article

Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and supportvector machine

Ali Reza GHANIZADEH, Hakime ABBASLOU, Amir Tavana AMLASHI, Pourya ALIDOUST

Journal Article

Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA

Xin CHEN, Ding WANG, Rui-rui LIU, Jie-xin YIN, Ying WU

Journal Article

Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

Journal Article