Table 2 Previous studies on preliminary... | Emerald Publishing

Table 2

Previous studies on preliminary bridge design and prediction of bridge characteristics using the tools in Table 1

Author	Prediction	Tools	Result
Hong et al. (2002)	Preliminary structural design of cable-stayed bridges	Neural networks	Multilevel neural networks for preliminary structural design; initial input: bridge length, clear height, bridge width
Andrade et al. (2003)	Design of highway bridges	Case-based reasoning (CBR), neural networks	A model, a framework and an implemented system for design integrating CBR and machine learning tools such as neural networks; results similar to real values
Jootoo and Lattanzi (2017)	Bridge type classification	Bayesian networks	Artificial approaches can be used to predict bridge type in the preliminary design phases; four input variables: material type, average span length, deck structure type, maximum span length
Singer et al. (2016)	Bridge characteristics	Bayesian networks	Bayesian networks seem suitable for preliminary bridge design; no real data were utilised

Author	Prediction	Tools	Result
Hong et al. (2002)	Preliminary structural design of cable-stayed bridges	Neural networks	Multilevel neural networks for preliminary structural design; initial input: bridge length, clear height, bridge width
Andrade et al. (2003)	Design of highway bridges	Case-based reasoning (CBR), neural networks	A model, a framework and an implemented system for design integrating CBR and machine learning tools such as neural networks; results similar to real values
Jootoo and Lattanzi (2017)	Bridge type classification	Bayesian networks	Artificial approaches can be used to predict bridge type in the preliminary design phases; four input variables: material type, average span length, deck structure type, maximum span length
Singer et al. (2016)	Bridge characteristics	Bayesian networks	Bayesian networks seem suitable for preliminary bridge design; no real data were utilised