Machine learning algorithms for structural performance classifications and predictions: Application to reinforced masonry shear walls
暂无分享,去创建一个
[1] Mohamed A. Shahin,et al. Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Directions , 2012 .
[2] Shengyong Chen,et al. Artificial Intelligence in Civil Engineering , 2012 .
[3] Salvador García Muñoz,et al. Data-based latent variable methods for process analysis, monitoring and control , 2005, Comput. Chem. Eng..
[4] Francesco Micelli,et al. Analytical model based on artificial neural network for masonry shear walls strengthened with FRM systems , 2016 .
[5] Kevin P. Murphy,et al. Machine learning - a probabilistic perspective , 2012, Adaptive computation and machine learning series.
[6] Anirban DasGupta,et al. Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics , 2011 .
[7] Marwan T. Shedid,et al. Behavior of Fully Grouted Reinforced Concrete Masonry Shear Walls Failing in Flexure : Experimental Results , 2008 .
[8] Wael W. El-Dakhakhni,et al. Seismic risk assessment of reinforced masonry structural wall systems using multivariate data analysis , 2017 .
[9] John W. Wallace,et al. Displacement-Based Design of Slender Reinforced Concrete Structural Walls—Experimental Verification , 2004 .
[10] Julián Carrillo,et al. Backbone Model for Performance-Based Seismic Design of RC Walls for Low-Rise Housing , 2012 .
[11] David C. Hoaglin,et al. Applications, basics, and computing of exploratory data analysis , 1983 .
[12] Mark Dougherty,et al. A REVIEW OF NEURAL NETWORKS APPLIED TO TRANSPORT , 1995 .
[13] Robert G. Drysdale,et al. Masonry Structures: Behavior and Design , 1993 .
[14] Z. Geem. Particle-swarm harmony search for water network design , 2009 .
[15] Jose M. Adam,et al. Prediction of the shear strength of reinforced masonry walls using a large experimental database and artificial neural networks , 2016 .
[16] Chuntian Cheng,et al. Real-Time Prediction of Water Stage with Artificial Neural Network Approach , 2002, Australian Joint Conference on Artificial Intelligence.
[17] Jack P. Moehle,et al. Ductility and Detailing Requirements of Bearing Wall Buildings , 1992 .
[18] Francesco Micelli,et al. An Artificial Neural Networks model for the prediction of the compressive strength of FRP-confined concrete circular columns , 2017 .
[19] Wael W. El-Dakhakhni,et al. Influence of Floor Diaphragm–Wall Coupling on the System-Level Seismic Performance of an Asymmetrical Reinforced Concrete Block Building , 2016 .
[20] Mehmet Polat Saka,et al. Optimum design of cellular beams using harmony search and particle swarm optimizers , 2011 .
[21] Jong-Su Jeon,et al. Artificial neural network based multi-dimensional fragility development of skewed concrete bridge classes , 2018 .
[22] Ming Zhong,et al. Lane-based short-term urban traffic forecasting with GA designed ANN and LWR models , 2017 .
[23] Mjn Priestley,et al. Performance based seismic design , 2000 .
[24] Kenneth J. Elwood,et al. Backbone Model for Confined Masonry Walls for Performance-Based Seismic Design , 2009 .
[25] Mervyn J. Kowalsky,et al. Displacement-based seismic design of structures , 2007 .
[26] Richard E. Klingner,et al. Seismic Performance of Cantilever-Reinforced Concrete Masonry Shear Walls , 2014 .
[27] Hany Mohamed Seif ElDin. In-Plane Shear Behaviour of Fully Grouted Reinforced Masonry Shear Walls , 2016 .
[28] Ronen I. Brafman,et al. Partial-Order Planning with Concurrent Interacting Actions , 2011, J. Artif. Intell. Res..
[29] Akbar A. Javadi,et al. Applications of artificial intelligence and data mining techniques in soil modeling , 2009 .
[30] F. Cannizzaro,et al. Seismic collapse prediction of frame structures by means of genetic algorithms , 2016 .
[31] P. B. Shing,et al. Inelastic Behavior of Concrete Masonry Shear Walls , 1989 .
[32] Ying Wang,et al. Prediction of Moment Redistribution in Statically Indeterminate Reinforced Concrete Structures Using Artificial Neural Network and Support Vector Regression , 2018, Applied Sciences.
[33] Maria Fox,et al. PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains , 2003, J. Artif. Intell. Res..
[34] J. Ingham,et al. Experimental In-Plane Shear Strength Investigation of Reinforced Concrete Masonry Walls , 2006 .
[35] Mohamed A. Shahin,et al. State-of-the-art review of some artificial intelligence applications in pile foundations , 2016 .
[36] Sotiris B. Kotsiantis,et al. Supervised Machine Learning: A Review of Classification Techniques , 2007, Informatica.
[37] Wilson H. Tang,et al. Probability Concepts in Engineering: Emphasis on Applications to Civil and Environmental Engineering , 2006 .
[38] Hani S. Mahmassani,et al. ARTIFICIAL INTELLIGENCE-BASED SYSTEM REPRESENTATION AND SEARCH PROCEDURES FOR TRANSIT ROUTE NETWORK DESIGN , 1992 .
[39] J. P. Moehle,et al. Displacement-Based Design of RC Structures Subjected to Earthquakes , 1992 .