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least square method 4

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in-situ hydrothermal deoxygenation 1

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Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path None

Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, Wasim Ullah KHAN

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2,   Pages 246-259 doi: 10.1631/FITEE.1601028

Abstract: Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for

Keywords： Active noise control (ANC)     Filtered extended least mean square (FXLMS)     Memetic computing     Genetic algorithms    

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Learning deep IA bidirectional intelligence Personal View

Lei XU

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 558-562 doi: 10.1631/FITEE.1900541

Abstract: There has been a framework sketched for learning deep bidirectional intelligence. The framework has an inbound that features two actions: one is the acquiring action, which gets inputs in appropriate patterns, and the other is A-S cognition, derived from the abbreviated form of words abstraction and self-organization, which abstracts input patterns into concepts that are labeled and understood by self-organizing parts involved in the concept into structural hierarchies. The top inner domain accommodates relations and a priori knowledge with the help of the A-I thinking action that is responsible for the accumulation-amalgamation and induction-inspiration. The framework also has an outbound that comes with two actions. One is called I-S reasoning, which makes inference and synthesis (I-S) and is responsible for performing various tasks including image thinking and problem solving, and the other is called the interacting action, which controls, communicates with, and inspects the environment. Based on this framework, we further discuss the possibilities of design intelligence through synthesis reasoning.

Keywords： Abstraction     Least mean square error reconstruction (Lmser)     Cognition     Image thinking     Abstract thinking    

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Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

Frontiers in Energy 2016, Volume 10, Issue 1,   Pages 105-113 doi: 10.1007/s11708-016-0393-y

Abstract: the day-ahead electricity price forecasting using the artificial neural networks (ANN) and weighted leastsquare (WLS) technique in the restructured electricity markets.

Keywords： day-ahead electricity markets     price forecasting     load forecasting     artificial neural networks     load serving entities    

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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 vectormachine,and develops algorithm of the extended prediction model.Prediction examples of two time-seriesshow that the extended model is more effective.Therefore it improves the value of the prediction methodof least square support vector machine.

Keywords： least square support vector machine     generalization     time series     forecasting    

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Theoretical prediction and validation of global horizontal solar irradiance for a tropical climate in India

Sivasankari SUNDARAM,Jakka SARAT CHANDRA BABU

Frontiers in Energy 2015, Volume 9, Issue 3,   Pages 311-321 doi: 10.1007/s11708-015-0369-3

Abstract: The proposed regression models were validated by the significance of statistical indicators such as meanbias error, root mean square error and mean percentage error from the predicted and the actual values

Keywords： global horizontal irradiance (GHI)     mean bias error     root mean square error     mean percentage error     coefficient    

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The S-N Curve Fitted by the Least Square Method Considering the Effect of Length of the Confidence Interval

Yang Xiaohua,Jin Ping,Yao Weixing

Strategic Study of CAE 2004, Volume 6, Issue 4,   Pages 41-43

Abstract: Founding on physical mechanism, this paper presents a weighted least square method in which the weighThe calculating results show that the S-N curve which is gained by the least square method consideringof the confidence interval is more reliable and secure than the S-N curve which is gained by general leastsquare method.

Keywords： confidence interval     fatigue life     least square method     S-N curve    

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Properties of a general quaternion-valued gradient operator and its applications to signal processing

Meng-di Jiang, Yi Li, Wei Liu,w.liu@sheffield.ac.uk

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 2,   Pages 83-95 doi: 10.1631/FITEE.1500334

Abstract: As an application, the derivation of the least mean square algorithm and a nonlinear adaptive algorithm

Keywords： Quaternion     Gradient operator     Signal processing     Least mean square (LMS) algorithm     Nonlinear adaptive    

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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 (LSSVMIn particular, three evaluation indexes including coefficient of determination, mean absolute percentageerror, and mean square error indicate that fitting precision of the machine learning-based failure criterion

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

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Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network

T. Chandra Sekhara REDDY

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 4,   Pages 490-503 doi: 10.1007/s11709-017-0445-3

Abstract: This paper is aimed at adapting Artificial Neural Networks (ANN) to predict the strength properties of SIFCON containing different minerals admixture. The investigations were done on 84 SIFCON mixes, and specimens were cast and tested after 28 days curing. The obtained experimental data are trained using ANN which consists of 4 input parameters like Percentage of fiber (PF), Aspect Ratio (AR), Type of admixture (TA) and Percentage of admixture (PA). The corresponding output parameters are compressive strength, tensile strength and flexural strength. The predicted values obtained using ANN show a good correlation between the experimental data. The performance of the 4-14-3 architecture was better than other architectures. It is concluded that ANN is a highly powerful tool suitable for assessing the strength characteristics of SIFCON.

Keywords： artificial neural networks     root mean square error     SIFCON     silica fume     metakaolin     steel fiber    

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Optical plasma boundary reconstruction based on least squares for EASTTokamak None

Hao LUO, Zheng-ping LUO, Chao XU, Wei JIANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 9,   Pages 1124-1134 doi: 10.1631/FITEE.1700041

Abstract: image plane to the Tokamak poloidal plane by a mathematical model, which is optimally resolved by using least

Keywords： Optical boundary reconstruction     Boundary detection     Global contrast     Least square     EAST Tokamak    

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System identification of channel roughness for middle route project of south to north water diversion

Yang Kailin,Wang Yisen

Strategic Study of CAE 2012, Volume 14, Issue 11,   Pages 17-23

Abstract: radius R, and deduce the linear model by means of the mathematical transformation to make use of the leastsquare method for the identification.

Keywords： channel     roughness     system identification     least square method    

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Prediction of performance, combustion and emission characteristics of diesel-thermal cracked cashew nut shell liquid blends using artificial neural network

Arunachalam VELMURUGAN,Marimuthu LOGANATHAN,E. James GUNASEKARAN

Frontiers in Energy 2016, Volume 10, Issue 1,   Pages 114-124 doi: 10.1007/s11708-016-0394-x

Abstract: The mean square error value (MSE) is 0.005621 and the regression value of is 0.99316 for training,

Keywords： cashew nut shell liquid (CNSL)     artificial neural networks (ANN)     thermal cracking     mean square error (MSE    

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Signal separation technology for diphase opposition giant magnetostrictive self-sensing actuator

Xinhua WANG, Shuwen SUN, Jian ZHEN, Qianyi YA, Deguo WANG,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 176-183 doi: 10.1007/s11465-010-0001-5

Abstract: balance separation technology for the giant magnetostrictive self-sensing actuator comes true by the leastmeans square (LMS) self-adapting algorithm.

Keywords： giant magnetostrictive material (GMM) self-sensing actuator     least means square (LMS) self-adapting algorithm    

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Modified Performance Index Method for Parameter Estimation for Industrial Process with Time-varying

Zhang Chenghui

Strategic Study of CAE 2001, Volume 3, Issue 11,   Pages 54-59

Abstract: based on modified performance index is proposed for time-varying process to avoid the ill-condition of leastBased on the new method,a series of new recursive algorithms such as the new recursive least squares

Keywords： parameter estimation     method of calculation     least square method     time-varying system     industrial production    

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Calculations of narrow-band transimissities and the Planck mean absorption coefficients of real gases

Huaqiang CHU, Mingyan GU, Huaichun ZHOU, Fengshan LIU

Frontiers in Energy 2014, Volume 8, Issue 1,   Pages 41-48 doi: 10.1007/s11708-013-0292-4

Abstract: The Planck mean absorption coefficients of CO , H O, CO, and CH in the temperature range of 300 to 2500The SNB model was also used to calculate the Planck mean absorption coefficients of these four radiatingThe LBL results of the Planck mean absorption coefficient were compared with the classical results of

Keywords： transimissity     HITEMP     HITRAN     Planck mean absorption coefficients    

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Title Author Date Type Operation

Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path

Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, Wasim Ullah KHAN

Journal Article

Learning deep IA bidirectional intelligence

Lei XU

Journal Article

Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

Journal Article

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

Xiang Xiaodong

Journal Article

Theoretical prediction and validation of global horizontal solar irradiance for a tropical climate in India

Sivasankari SUNDARAM,Jakka SARAT CHANDRA BABU

Journal Article

The S-N Curve Fitted by the Least Square Method Considering the Effect of Length of the Confidence Interval

Yang Xiaohua,Jin Ping,Yao Weixing

Journal Article

Properties of a general quaternion-valued gradient operator and its applications to signal processing

Meng-di Jiang, Yi Li, Wei Liu,w.liu@sheffield.ac.uk

Journal Article

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

Shiguo XIAO; Shaohong LI

Journal Article

Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network

T. Chandra Sekhara REDDY

Journal Article

Optical plasma boundary reconstruction based on least squares for EASTTokamak

Hao LUO, Zheng-ping LUO, Chao XU, Wei JIANG

Journal Article

System identification of channel roughness for middle route project of south to north water diversion

Yang Kailin,Wang Yisen

Journal Article

Prediction of performance, combustion and emission characteristics of diesel-thermal cracked cashew nut shell liquid blends using artificial neural network

Arunachalam VELMURUGAN,Marimuthu LOGANATHAN,E. James GUNASEKARAN

Journal Article

Signal separation technology for diphase opposition giant magnetostrictive self-sensing actuator

Xinhua WANG, Shuwen SUN, Jian ZHEN, Qianyi YA, Deguo WANG,

Journal Article

Modified Performance Index Method for Parameter Estimation for Industrial Process with Time-varying

Zhang Chenghui

Journal Article

Calculations of narrow-band transimissities and the Planck mean absorption coefficients of real gases

Huaqiang CHU, Mingyan GU, Huaichun ZHOU, Fengshan LIU

Journal Article