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An ANN-exhaustive-listing method for optimization of multiple building shapes and envelope properties

Yaolin LIN, Wei YANG

Frontiers in Energy 2021, Volume 15, Issue 2,   Pages 550-563 doi: 10.1007/s11708-019-0607-1

Abstract: This paper attempts to develop an innovative ANN (artificial neural network)-exhaustive-listing methodtreated separately to achieve sufficient accuracy of prediction of thermal performance and that the ANN

Keywords： ANN (artificial neural network)     exhaustive-listing     building shape     optimization     thermal load     thermal comfort    

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Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

Frontiers in Energy 2013, Volume 7, Issue 4,   Pages 468-478 doi: 10.1007/s11708-013-0282-6

Abstract: solved to perform the unit commitment (UC) based on frequency prediction by using artificial neural network(ANN) with the objective to minimize the overall system cost of the state utility.

Keywords： artificial neural network (ANN)     frequency prediction     availability-based tariff (ABT)     generation scheduling    

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QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 1,   Pages 25-36 doi: 10.1007/s11709-022-0908-z

Abstract: a method to optimize TBM control parameters using an improved loss function-based artificial neural network(ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein.Inspired by the regularization technique, a custom artificial neural network (ANN) loss function basedTBM performance indicators is developed in the form of a penalty function to adjust the output of the networkResults show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases

Keywords： boring machine     control parameter optimization     quantum particle swarm optimization     artificial neural network    

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Experimental investigation and ANN modeling on improved performance of an innovative method of using

Srinivasan CHANDRASEKARAN, Arunachalam AMARKARTHIK, Karuppan SIVAKUMAR, Dhanasekaran SELVAMUTHUKUMARAN, Shaji SIDNEY

Frontiers in Energy 2013, Volume 7, Issue 3,   Pages 279-287 doi: 10.1007/s11708-013-0268-4

Abstract: The device was modeled in artificial neural network (ANN), the heave response for various parametersIt was found that the ANN model could predict the heave response with an accuracy of 99%.

Keywords： wave energy     point absorbers     heaving body     non-floating object     heave response ratio     artificial neural network(ANN)    

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Liquefaction assessment using microtremor measurement, conventional method and artificial neural network

Sadegh REZAEI,Asskar Janalizadeh CHOOBBASTI

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 3,   Pages 292-307 doi: 10.1007/s11709-014-0256-8

Abstract: Also, the results obtained by the artificial neural network (ANN) were compared with microtremor measurement

Keywords： liquefaction     microtremor     vulnerability index     artificial neural networks (ANN)     microzonation    

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RBF-ANN-Based forecast method of transmutation of wall rock on multi-arch tunne

Xiao Zhiwang,Zhong Denghua

Strategic Study of CAE 2008, Volume 10, Issue 7,   Pages 77-81

Abstract: According to the characteristics of feed forward neural network of radial basis function to construct

Keywords： tunnel     deformation of wall rock     deformation forecast     radial basis function (RBF)     artificial neural network(ANN)    

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Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II

Ravindra Nath YADAV, Vinod YADAVA, G.K. SINGH

Frontiers of Mechanical Engineering 2013, Volume 8, Issue 3,   Pages 319-332 doi: 10.1007/s11465-013-0269-3

Abstract: The combined approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm-IIElectrical Discharge Diamond face Grinding (EDDFG) have been studied using a hybrid methodology of ANN-NSGA-IIIn this study, ANN has been used for modeling while NSGA-II is used to optimize the control parametersThe results have shown that the developed ANN model is capable to predict the output responses withinIt has also been found that hybrid approach of ANN-NSGA-II gives a set of optimal solutions for getting

Keywords： hybrid machining processes (HMPs)     electrical discharge diamond grinding (EDDG)     artificial neural network(ANN)     genetic algorithm     modeling and optimization    

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ANN-based empirical modelling of pile behaviour under static compressive loading

Abdussamad ISMAIL

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 4,   Pages 594-608 doi: 10.1007/s11709-017-0446-2

Abstract: In this paper, an empirical model based on the product-unit neural network (PUNN) is developed to predict

Keywords： piles in compression     load-deformation behaviour     product-unit neural network    

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Short-term Load Forecasting Using Neural Network

Luo Mei

Strategic Study of CAE 2007, Volume 9, Issue 5,   Pages 77-80

Abstract: text-align: justify;">Based on the load data of meritorious power of some area power system,  three BP ANNthe optimized function,  an optimized L-M algorithm, which can accelerate the training of neural network Bayesian regularization can overcome the over fitting and improve the generalization of ANN.

Keywords： short-term load forecasting(STLF)     ANN     Levenberg-Marquardt     Bayesian regularization     optimized algorithms    

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Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 133-136 doi: 10.1007/s11709-013-0202-1

Abstract: A comparative study has been carried out between the developed GPR and Artificial Neural Network (ANN

Keywords： unsaturated soil     effective stress parameter     Gaussian process regression (GPR)     artificial neural network(ANN)     variance    

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Theory analysis and system identification methods on thermal dynamics characteristics of ballscrews

XIA Junyong, HU Youmin, WU Bo, SHI Tielin

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 4,   Pages 408-415 doi: 10.1007/s11465-008-0061-y

Abstract: methods for system identification (the least square system identification and BP artificial neural network(ANN) system identification) are put forward to establish a dynamic characteristic model of thermalComparing the results of the two identification methods, the BP ANN system identification is more precise

Keywords： square system     network     vertical miller     transfer     ANN    

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Predicting the capacity of perfobond rib shear connector using an ANN model and GSA method

Guorui SUN; Jun SHI; Yuang DENG

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 10,   Pages 1233-1248 doi: 10.1007/s11709-022-0878-1

Abstract: Due to recent advances in the field of artificial neural networks (ANN) and the global sensitivity analysisperformance of perfobond rib shear connectors (PRSCs) is predicted based on the back propagation (BP) ANNThe results predicted by the ANN models and empirical equations were compared, and the factors affectingThe results show that the use of ANN model optimization by GA method has fewer errors compared to the

Keywords： perfobond rib shear connector     shear strength     ANN model     global sensitivity analysis    

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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: wind power equation, concept of power curve, response surface methodology (RSM) and artificial neural network(ANN), and the results have been compared.based on the concept of power curve, the manufacturer’s power curve, and to develop RSM as well as ANNblade pitch angle, rotor speed and wind direction have been considered as input variables for RSM and ANNProper selection of input variables and capability of ANN to map input-output relationships have resulted

Keywords： curve     method of least squares     cubic spline interpolation     response surface methodology     artificial neural network(ANN)    

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Food Safety and Health

Martin Cole, Mary Ann Augustin

Engineering 2020, Volume 6, Issue 4,   Pages 391-392 doi: 10.1016/j.eng.2020.01.010

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Application of Artificial Neural Network to Engineering Project Management

Wang Yingluo,Yang Yaohong

Strategic Study of CAE 2004, Volume 6, Issue 7,   Pages 26-33

Abstract:

Applications of ANN to engineering project management were summarized, including prediction and evaluationexisting in application were summarized and analyzed, some suggestions on how to develop application of ANN

Keywords： engineering project management     ANN     prediction     optimization     DS    

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Title Author Date Type Operation

An ANN-exhaustive-listing method for optimization of multiple building shapes and envelope properties

Yaolin LIN, Wei YANG

Journal Article

Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

Journal Article

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

Journal Article

Experimental investigation and ANN modeling on improved performance of an innovative method of using

Srinivasan CHANDRASEKARAN, Arunachalam AMARKARTHIK, Karuppan SIVAKUMAR, Dhanasekaran SELVAMUTHUKUMARAN, Shaji SIDNEY

Journal Article

Liquefaction assessment using microtremor measurement, conventional method and artificial neural network

Sadegh REZAEI,Asskar Janalizadeh CHOOBBASTI

Journal Article

RBF-ANN-Based forecast method of transmutation of wall rock on multi-arch tunne

Xiao Zhiwang,Zhong Denghua

Journal Article

Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II

Ravindra Nath YADAV, Vinod YADAVA, G.K. SINGH

Journal Article

ANN-based empirical modelling of pile behaviour under static compressive loading

Abdussamad ISMAIL

Journal Article

Short-term Load Forecasting Using Neural Network

Luo Mei

Journal Article

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Journal Article

Theory analysis and system identification methods on thermal dynamics characteristics of ballscrews

XIA Junyong, HU Youmin, WU Bo, SHI Tielin

Journal Article

Predicting the capacity of perfobond rib shear connector using an ANN model and GSA method

Guorui SUN; Jun SHI; Yuang DENG

Journal Article

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

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

Journal Article

Food Safety and Health

Martin Cole, Mary Ann Augustin

Journal Article

Application of Artificial Neural Network to Engineering Project Management

Wang Yingluo,Yang Yaohong

Journal Article