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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:

The vibration of powerhouse structures is mainly induced by hydraulics factors, mechanical and electromagnetic factors of the generating unit. It nonlinearly couples with the generating unit. Based on prototype observation data of Ertan Hydropower Station, the paper analyzes the coupling effect between vibration of units and powerhouse,and then the vibration response forecasting model of the powerhouse is built based on LS-SVM optimized by particle swarm optimization algorithm, and the prediction results are coincide with the observed data. Further, the paper introduces the running water head as an input divisor into the intelligent prediction model while the forecasting range is extended, and the result is satisfactory.

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

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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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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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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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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: regression (SWR), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the leastsquares support vector machine (LS-SVM) model for the prediction of BP reactivity to an unsupported

Keywords： stepwise regression     Artificial neural network (ANN)     Adaptive neuro-fuzzy inference system (ANFIS)     Leastsquares support vector machine (LS-SVM)    

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Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

Frontiers in Energy 2012, Volume 6, Issue 4,   Pages 394-402 doi: 10.1007/s11708-012-0211-0

Abstract: This paper investigates the capability of support vector machines (SVM) for prediction of fault classification

Keywords： support vector machines (SVM)     structural risk minimization (SRM)     equivalent capacity margin (ECM)     restoration    

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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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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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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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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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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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Comparison of modeling methods for wind power prediction: a critical study

Rashmi P. SHETTY, A. SATHYABHAMA, P. Srinivasa PAI

Frontiers in Energy 2020, Volume 14, Issue 2,   Pages 347-358 doi: 10.1007/s11708-018-0553-3

Abstract: Prediction of power generation of a wind turbine is crucial, which calls for accurate and reliable models. In this work, six different models have been developed based on wind power equation, concept of power curve, response surface methodology (RSM) and artificial neural network (ANN), and the results have been compared. To develop the models based on the concept of power curve, the manufacturer’s power curve, and to develop RSM as well as ANN models, the data collected from supervisory control and data acquisition (SCADA) of a 1.5 MW turbine have been used. In addition to wind speed, the air density, blade pitch angle, rotor speed and wind direction have been considered as input variables for RSM and ANN models. Proper selection of input variables and capability of ANN to map input-output relationships have resulted in an accurate model for wind power prediction in comparison to other methods.

Keywords： power curve     method of least squares     cubic spline interpolation     response surface methodology     artificial    

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New decentralized control technique based on substructure and LQG approaches

Ying LEI, Ying LIN,

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 4,   Pages 386-392 doi: 10.1007/s11465-009-0041-x

Abstract: An algorithm of recursive least squares estimation for the unknown excitation is proposed.

Keywords： substructures     decentralized control     linear quadratic Gaussian (LQG)     Kalman filter     unknown input     least-squares    

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Title Author Date Type Operation

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

Lian Jijian,He Longjun,Wang Haijun

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

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

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

Xiang Xiaodong

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

Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

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

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

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

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

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

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

Comparison of modeling methods for wind power prediction: a critical study

Rashmi P. SHETTY, A. SATHYABHAMA, P. Srinivasa PAI

Journal Article

New decentralized control technique based on substructure and LQG approaches

Ying LEI, Ying LIN,

Journal Article