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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) ANNmodel, the Genetic Algorithm (GA) method and GSA method.The 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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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: and analyzes some main factors influencing seismic disasters risk at first, and then, the forecasting modelThe case shows that the model is practical and effective.

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: structures based on vibration analysis using the Finite Element Method (FEM) and Artificial Neural Network (ANNANN 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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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: perform the unit commitment (UC) based on frequency prediction by using artificial neural network (ANNThe performance of the frequency predictor model has been evaluated based on the absolute percentageThe proposed predicted frequency sensitive GS model is applied to the system of Indian state of Tamilnadu

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

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

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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: optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANNInspired 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 ANNRock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-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 neural network     tunneling energy efficiency    

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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: key of forecasting transmutation of wall rock correctly is to construct the reasonable mathematics modelthe characteristics of feed forward neural network of radial basis function to construct the forecast model

Keywords： 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： machining processes (HMPs)     electrical discharge diamond grinding (EDDG)     artificial neural network (ANN    

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The Power of an Idea: The International Impacts of the Grand Challenges for Engineering Views & Comments

., Dame Ann Dowling, Ji Zhou

Engineering 2016, Volume 2, Issue 1,   Pages 4-7 doi: 10.1016/J.ENG.2016.01.025

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Delivering food safety

Kaye BASFORD,Richard BENNETT,Joanne DALY,Mary Ann AUGUSTIN,Snow BARLOW,Tony GREGSON,Alice LEE,Deli CHEN

Frontiers of Agricultural Science and Engineering 2017, Volume 4, Issue 1,   Pages 1-4 doi: 10.15302/J-FASE-2016123

Abstract: A delegation from the Australian Academy of Technological Sciences and Engineering traveled to Beijing in April 2016 to jointly run a workshop on technology advances in food safety with the Chinese Academy of Engineering. This brief summary from the Australian delegation identifies the pyramid of inter- locking issues which must be addressed to deliver food safety. Systems and technology provide the necessary base, on which culture and then trust can be built to facilitate the delivery of food safety now and in the future.

Keywords： culture     food safety     systems     technology     trust    

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Processing and analysis of data from microwave humidity sounder onboard FY-3A satellite

He Jieying,Zhang Shengwei

Strategic Study of CAE 2013, Volume 15, Issue 10,   Pages 47-53

Abstract: The paper constructs an inversion model using artificial neural network (ANN) algorithm, and makes comparisonThe results demonstrate that the model can be operated successfully.

Keywords： MWHS     FY-3A     ANN     water vapor density    

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Nitrogen removal efficiencies and microbial communities in full-scale IFAS and MBBR municipal wastewater treatment plants at high COD:N ratio

Naluporn Kangwannarakul, Pongsak (Lek) Noophan, Tamao Kasahara, Akihiko Terada, Junko Munakata-Marr, Linda Ann

Frontiers of Environmental Science & Engineering 2020, Volume 14, Issue 6, doi: 10.1007/s11783-020-1374-2

Abstract: Abstract • Two IFAS and two MBBR full-scale systems (high COD:N ratio 8:1) were characterized. • High specific surface area carriers grew and retained slow-growing nitrifiers. • High TN removal is related to high SRT and low DO concentration in anoxic tanks. The relative locations of AOB, NOB, and DNB were examined for three different kinds of carriers in two types of hybrid biofilm process configurations: integrated fixed-film activated sludge (IFAS) and moving bed biofilm reactor (MBBR) processes. IFAS water resource recovery facilities (WRRFs) used AnodkalnessTM K1 carriers (KC) at Broomfield, Colorado, USA and polypropylene resin carriers (RC) at Fukuoka, Japan, while MBBR WRRFs used KC carriers at South Adams County, Colorado, USA and sponge carriers (SC) at Saga, Japan. Influent COD to N ratios ranged from 8:1 to 15:1. The COD and BOD removal efficiencies were high (96%–98%); NH4+-N and TN removal efficiencies were more varied at 72%–98% and 64%–77%, respectively. The extent of TN removal was higher at high SRT, high COD:N ratio and low DO concentration in the anoxic tank. In IFAS, RC with high specific surface area (SSA) maintained higher AOB population than KC. Sponge carriers with high SSA maintained higher overall bacteria population than KC in MBBR systems. However, the DNB were not more abundant in high SSA carriers. The diversity of AOB, NOB, and DNB was fairly similar in different carriers. Nitrosomonas sp. dominated over Nitrosospira sp. while denitrifying bacteria included Rhodobacter sp., Sulfuritalea sp., Rubrivivax sp., Paracoccus sp., and Pseudomonas sp. The results from this work suggest that high SRT, high COD:N ratio, low DO concentration in anoxic tanks, and carriers with greater surface area may be recommended for high COD, BOD and TN removal in WRRFs with IFAS and MBBR systems.

Keywords： IFAS     MBBR     AnodkalnessTM K1 carrier     Polypropylene resin carrier     Sponge carrier    

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Synthetic optimization modeling on mining and utilization of multi-deposits in Gushan mine area

Cai Sijing,Wang Wenxiao,Zheng Minggui

Strategic Study of CAE 2011, Volume 13, Issue 3,   Pages 56-62

Abstract: a mine area by systematic and dynamic considering of mine full-life process, a synthetic optimizing modelof artificial neutral network (ANN) export system is set up.By using the model ,a synthetic optimization

Keywords： Gushan mine area     multi-deposits mining     full-scale mining concept     ANNexport system model    

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Title Author Date Type Operation

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

Guorui SUN; Jun SHI; Yuang DENG

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

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

Food Safety and Health

Martin Cole, Mary Ann Augustin

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

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

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

The Power of an Idea: The International Impacts of the Grand Challenges for Engineering

., Dame Ann Dowling, Ji Zhou

Journal Article

Delivering food safety

Kaye BASFORD,Richard BENNETT,Joanne DALY,Mary Ann AUGUSTIN,Snow BARLOW,Tony GREGSON,Alice LEE,Deli CHEN

Journal Article

Processing and analysis of data from microwave humidity sounder onboard FY-3A satellite

He Jieying,Zhang Shengwei

Journal Article

Nitrogen removal efficiencies and microbial communities in full-scale IFAS and MBBR municipal wastewater treatment plants at high COD:N ratio

Naluporn Kangwannarakul, Pongsak (Lek) Noophan, Tamao Kasahara, Akihiko Terada, Junko Munakata-Marr, Linda Ann

Journal Article

Synthetic optimization modeling on mining and utilization of multi-deposits in Gushan mine area

Cai Sijing,Wang Wenxiao,Zheng Minggui

Journal Article