Improving the conversion accuracy between bridge element conditions and NBI ratings using deep convolutional neural networks
暂无分享,去创建一个
[1] Vipin Kumar,et al. Parallel Formulations of Decision-Tree Classification Algorithms , 2004, Data Mining and Knowledge Discovery.
[2] Samuel Labi,et al. Modeling Deterioration of Bridge Components with Binary Probit Techniques with Random Effects , 2016 .
[3] Graziano Fiorillo,et al. Application of Machine Learning Techniques for the Analysis of National Bridge Inventory and Bridge Element Data , 2019 .
[4] George Morcous,et al. Performance Prediction of Bridge Deck Systems Using Markov Chains , 2006 .
[5] John O Sobanjo,et al. Semi-Markov Models for the Deterioration of Bridge Elements , 2016 .
[6] Martin A. Riedmiller,et al. Advanced supervised learning in multi-layer perceptrons — From backpropagation to adaptive learning algorithms , 1994 .
[7] Bojidar Yanev,et al. Bridge Maintenance in New York City , 2011 .
[8] Li Deng,et al. A tutorial survey of architectures, algorithms, and applications for deep learning , 2014, APSIPA Transactions on Signal and Information Processing.
[9] Abba G. Lichtenstein,et al. The Silver Bridge Collapse Recounted , 1993 .
[10] Richard Shepard,et al. Bridge Management for the 21st Century , 2000 .
[11] Alfred A. Yousif,et al. Application of knowledge-based expert systems for rating highway bridges , 1995 .
[12] Stefan Fritsch,et al. neuralnet: Training of Neural Networks , 2010, R J..
[13] Sylvester Inkoom,et al. Bridge Health Index: Study of Element Condition States and Importance Weights , 2017 .
[14] Xiaolin Li,et al. GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text , 2017, Bioinform..
[15] Oral Büyüköztürk,et al. Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks , 2017, Comput. Aided Civ. Infrastructure Eng..
[16] Robert J. Marks,et al. Inversion of feedforward neural networks: algorithms and applications , 1999, Proc. IEEE.
[17] Basak Aldemir Bektas. Use of Recursive Partitioning to Predict National Bridge Inventory Condition Ratings from National Bridge Elements Condition Data , 2017 .
[18] Wenyu Liu,et al. Cascaded Segmentation-Detection Networks for Text-Based Traffic Sign Detection , 2018, IEEE Transactions on Intelligent Transportation Systems.
[19] Basak Aldemir Bektas,et al. Using Classification Trees for Predicting National Bridge Inventory Condition Ratings , 2013 .
[20] Kumares C. Sinha,et al. Comparison of Methodologies to Predict Bridge Deterioration , 1997 .
[21] ChaYoung-Jin,et al. Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks , 2017 .
[22] Zhongjie Zhang,et al. Analysis of Past National Bridge Inventory Ratings for Predicting Bridge System Preservation Needs , 2004 .
[23] Yew-Chaye Loo,et al. Improving the reliability of a Bridge Management System (BMS) using an ANN-based Backward Prediction Model (BPM) , 2008 .
[24] George Morcous. Modeling Bridge Deck Deterioration by Using Decision Tree Algorithms , 2005 .