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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: the GS problem is solved to perform the unit commitment (UC) based on frequency prediction by using artificialneural 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: Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neuralnetwork (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 basedbackpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANNResults show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases

Keywords： tunnel boring machine     control parameter optimization     quantum particle swarm optimization     artificial    

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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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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： ocean wave energy     point absorbers     heaving body     non-floating object     heave response ratio     artificial neuralnetwork (ANN)    

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Research on Forecasting Model of Seismic Disaster Risk Based on GA-ANN

Liu Mingguang,Guo Zhanglin

Strategic Study of CAE 2006, Volume 8, Issue 3,   Pages 83-86

Abstract: disasters risk at first, and then, the forecasting model of seismic risk based on the genetic algorithm and artificial

Keywords： seismic disaster     factors of risk     artificial neural networks     genetic algorithm     forecasting    

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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: depth in steel beam structures based on vibration analysis using the Finite Element Method (FEM) and ArtificialNeural Network (ANN) combined with Butterfly Optimization Algorithm (BOA).ANN is quite successful in such identification issues, but it has some limitations, such as reductionThis 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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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:

The key of forecasting transmutation of wall rock correctly is to construct the reasonable mathematics model of time-distance curve from measuring data when distorting, which is hard to describe accurately with traditional method of recursive analysis. According to the characteristics of feed forward neural network of radial basis function to construct the forecast model of deformation of wall rock in multi-arch tunnel and cllso uses Matlab tool to solve the optimal problem. The engineering case at the end of this paper validates the method. For its fast solving the problem,more optimal results,and better forecasting effects,this method shows its advantages and feasibility.

Keywords： multi-arch tunnel     deformation of wall rock     deformation forecast     radial basis function (RBF)     artificialneural network (ANN)    

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Lateral-torsional buckling capacity assessment of web opening steel girders by artificial neural networks

Yasser SHARIFI,Sajjad TOHIDI

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 2,   Pages 167-177 doi: 10.1007/s11709-014-0236-z

Abstract: Artificial neural network (ANN) approach has been also employed to derive empirical formulae for predicting

Keywords： steel I-beams     lateral-torsional buckling     finite element (FE) method     artificial neural network (ANN) approach    

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of spinal lumbar interbody fusion cage subsidence using Taguchi method, finite element analysis, and artificial

Christopher John NASSAU, N. Scott LITOFSKY, Yuyi LIN

Frontiers of Mechanical Engineering 2012, Volume 7, Issue 3,   Pages 247-255 doi: 10.1007/s11465-012-0335-2

Abstract: No previous studies have utilized an artificial neural network (ANN) for the design of a spinal interbodyThe calculated subsidence is derived from the ANN objective function which is defined as the resultingThe ANN was found to have minimized the bone surface VMS, thereby optimizing the ALIF cage given theTherefore, the Taguchi-FEA-ANN approach can serve as an effective procedure for designing a spinal fusion

Keywords： anterior lumbar interbody fusion (ALIF)     artificial neural network (ANN)     finite element     interbody cage    

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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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combustion and emission characteristics of diesel-thermal cracked cashew nut shell liquid blends using artificial

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: This paper explores the use of artificial neural networks (ANN) to predict performance, combustion andThe ANN was used to predict eight different engine-output responses, namely brake thermal efficiencyThe ANN results show that there is a good correlation between the ANN predicted values and the experimentalThus the developed ANN model is fairly powerful for predicting the performance, combustion and exhaust

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

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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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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: developed based on wind power equation, concept of power curve, response surface methodology (RSM) and artificialneural 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： power curve     method of least squares     cubic spline interpolation     response surface methodology     artificialneural network (ANN)    

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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

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

Sadegh REZAEI,Asskar Janalizadeh CHOOBBASTI

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

Research on Forecasting Model of Seismic Disaster Risk Based on GA-ANN

Liu Mingguang,Guo Zhanglin

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

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

Xiao Zhiwang,Zhong Denghua

Journal Article

Lateral-torsional buckling capacity assessment of web opening steel girders by artificial neural networks

Yasser SHARIFI,Sajjad TOHIDI

Journal Article

of spinal lumbar interbody fusion cage subsidence using Taguchi method, finite element analysis, and artificial

Christopher John NASSAU, N. Scott LITOFSKY, Yuyi LIN

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

combustion and emission characteristics of diesel-thermal cracked cashew nut shell liquid blends using artificial

Arunachalam VELMURUGAN,Marimuthu LOGANATHAN,E. James GUNASEKARAN

Journal Article

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

Pijush Samui, Jagan J

Journal Article

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

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

Journal Article

Application of Artificial Neural Network to Engineering Project Management

Wang Yingluo,Yang Yaohong

Journal Article